Method for assessing risk of blood pressure during pregnancy, electronic device and readable storage medium

Abstract

The present application provides a method for assessing the risk of blood pressure during pregnancy, an electronic device, and a readable storage medium, and relates to the field of terminal technology. The method is applied to electronic devices, including: obtaining the prediction results of the blood circulation status, mental health status, and blood pressure fluctuation status of the next pregnancy cycle in the current pregnancy cycle; determining the risk assessment score of the blood pressure in the next pregnancy cycle based on the prediction results of the blood circulation status, mental health status, and blood pressure fluctuation status; when the risk assessment score is in the first interval, determining the blood pressure in the next pregnancy cycle as a risk-free level; when the risk assessment score is in the second interval, determining the blood pressure in the next pregnancy cycle as a risky level. Based on the above technical solution, the electronic device can predict and assess the blood pressure risk level of the next pregnancy cycle in the current pregnancy cycle, and can remind the user to seek medical treatment in time when there is a risk, which helps the user pay attention to their own health and prevent high blood pressure during pregnancy.

Description

Technical Field

[0001] The present application relates to the field of terminal technology, and in particular to a method for assessing blood pressure risk during pregnancy, an electronic device, and a readable storage medium. Background Art

[0002] Gestational hypertension refers to a group of diseases in which pregnancy and high blood pressure coexist. It is a common obstetric disease. The clinical manifestations of gestational hypertension are diverse, including high blood pressure, proteinuria, edema, and multiple organ damage throughout the body. In severe cases, convulsions (eclampsia) and coma may occur, which seriously affect the health of mother and child and is one of the main causes of maternal and perinatal mortality.

[0003] Currently, whether a pregnant woman suffers from gestational hypertension is mainly checked by measuring blood pressure, but it is difficult to assess in advance whether there is a risk of blood pressure during pregnancy through electronic devices carried by the user. Summary of the invention

[0004] The present application provides a method for assessing blood pressure risk during pregnancy, an electronic device, and a readable storage medium, which can effectively assess blood pressure risk during pregnancy. The technical solution is as follows:

[0005] In a first aspect, an embodiment of the present application provides a method for assessing blood pressure risk during pregnancy, which is applied to an electronic device. The method includes: obtaining prediction results of the blood circulation status, mental health status, and blood pressure fluctuation status of the next pregnancy cycle in the current pregnancy cycle; determining a risk assessment score for the blood pressure in the next pregnancy cycle based on the prediction results of the blood circulation status, mental health status, and blood pressure fluctuation status; when the risk assessment score is in a first interval, determining the risk level of the blood pressure in the next pregnancy cycle to be a non-risk level; when the risk assessment score is in a second interval, determining the risk level of the blood pressure in the next pregnancy cycle to be a risky level.

[0006] Based on the above technical solution, the electronic device can predict the blood circulation status, mental health status, and blood pressure fluctuation status of the next pregnancy cycle in the current pregnancy cycle, and obtain the prediction results. According to the prediction results of the blood circulation status, mental health status, and blood pressure fluctuation status of the next pregnancy cycle, the risk assessment score of the blood pressure in the next pregnancy cycle is determined, and then the blood pressure risk level of the next pregnancy cycle is determined based on the risk assessment score, so as to realize the risk prediction and assessment of the blood pressure in the next pregnancy cycle in the current pregnancy cycle. When the blood pressure risk level of the next pregnancy cycle is risky, the user can be reminded to seek medical treatment in time, which helps the user pay attention to their own health and prevent high blood pressure during pregnancy.

[0007] In combination with the first aspect, the second interval includes the third interval, the fourth interval, and the fifth interval in sequence, which are non-overlapping. When the risk assessment score is in the second interval, determining the risk level of blood pressure in the next pregnancy cycle as a risky level includes:

[0008] When the risk assessment score is in the third interval, the risk level of blood pressure in the next pregnancy cycle is determined to be the first risk level; when the risk assessment score is in the fourth interval, the risk level of blood pressure in the next pregnancy cycle is determined to be the second risk level; when the risk assessment score is in the fifth interval, the risk level of blood pressure in the next pregnancy cycle is determined to be the third risk level; based on the risk level of blood pressure in the next pregnancy cycle, prompt information corresponding to the first risk level, the second risk level or the third risk level is output.

[0009] By further dividing the risk level into a low risk level (first risk level), a medium risk level (second risk level) and a high risk level (third risk level), users can more clearly understand their health conditions through risk levels, which can improve user experience. It should be understood that the embodiment of the present application is only an exemplary division of the risk level into a low risk level, a medium risk level and a high risk level. In other implementations, the risk level may also be divided into fewer or more levels, for example, into a low risk level and a high risk level.

[0010] In combination with the first aspect, in certain implementations of the first aspect, prompt information corresponding to the first risk level, the second risk level, or the third risk level is output, including: displaying a first interface, the first interface including the risk level of blood pressure in the next pregnancy cycle and prompt information corresponding to the risk level of blood pressure in the next pregnancy cycle.

[0011] The electronic device may display corresponding prompt information on the user interface according to different risk levels. For example, the electronic device may display a first interface in an application, and the first interface includes a first risk level and corresponding prompt information, or a second risk level and corresponding prompt information, or a third risk level and corresponding prompt information. For example, the first interface may be a lock screen interface or a negative one screen, and the electronic device may display the determined blood pressure risk level for the next pregnancy cycle on the lock screen interface or the negative one screen to remind the user whether there is a risk, so that the user can obtain risk information in a timely manner.

[0012] In some implementations, the electronic device may also prompt the user of the pregnancy blood pressure risk level through voice.

[0013] In combination with the first aspect and the above-mentioned implementation methods, in certain implementation methods of the first aspect, the risk assessment score of the blood pressure in the next pregnancy cycle is determined according to the predicted results of the blood circulation status, the mental health status, and the blood pressure fluctuation status, including: determining the numerical values ​​corresponding to the predicted results of the blood circulation status, the mental health status, and the blood pressure fluctuation status, respectively, the numerical values ​​are used to measure the risk degree of different prediction results; determining the risk assessment score of the blood pressure in the next pregnancy cycle according to the numerical values ​​corresponding to the predicted results of the blood circulation status, the mental health status, and the blood pressure fluctuation status.

[0014] Exemplarily, the prediction results of blood circulation status can be divided into four categories: mild, moderate, moderately severe, and severe, and the corresponding values ​​are 0.1, 0.6, 0.8, and 1, respectively. The prediction results of mental health status can be divided into four categories: good, general, poor, and extremely poor, and the corresponding values ​​are 0.1, 0.2, 0.6, and 1, respectively. The prediction results of blood pressure fluctuation status can be divided into four categories: fluctuation range is less than 2 mmHg, fluctuation range is greater than or equal to 2 mmHg and less than 10 mmHg, fluctuation range is greater than or equal to 10 mmHg and less than 15 mmHg, and fluctuation range is greater than 20 mmHg, and the corresponding values ​​are 0.1, 0.2, 0.5, and 1, respectively. The larger the value, the worse the health status. After determining each prediction result, the corresponding value can be determined to calculate the risk assessment score. The risk level of blood pressure in the next pregnancy cycle is quantified by the risk assessment score, and the blood pressure risk level in the next pregnancy cycle can be obtained more accurately.

[0015] In combination with the first aspect and the above-mentioned implementation methods, in some implementation methods of the first aspect, obtaining a prediction result of the blood circulation state in the next pregnancy cycle includes: obtaining a first feature of the photoplethysmogram signal in the current pregnancy cycle, the first feature characterizing the contraction characteristics of the blood vessels and / or the blood volume characteristics; determining a prediction result of the blood circulation state in the next pregnancy cycle based on the first feature and the first model, the first model being used to predict the blood circulation state in the next pregnancy cycle.

[0016] In combination with the first aspect and the above-mentioned implementation methods, in some implementation methods of the first aspect, the first feature includes at least one of the following: peak transmission time between different wavelengths in two adjacent cardiac cycles, maximum rise speed transmission time between different wavelengths in two adjacent cardiac cycles, pulse wave amplitude ratio, amplitude ratio of pulse wave peak to trough, time interval between pulse wave peak and dicrotic wave trough.

[0017] The occurrence of gestational hypertension is closely related to changes in the blood circulation system of pregnant women. The blood circulation status can effectively reflect whether the user's blood pressure is at risk of increasing. In this application, the user's blood circulation status can be judged by a first feature that characterizes the contraction characteristics of the blood vessels and / or the blood volume characteristics. Among them, the first feature can be extracted by a photoplethysmography (PPG) signal, and the PPG signal can be collected by a PPG sensor.

[0018] The first model can be obtained through pre-training. Specifically, the first feature data of multiple pregnant users in each pregnancy cycle can be obtained through big data, and then the feature data of the previous pregnancy cycle of two adjacent pregnancy cycles is used as input, and the feature data of the next pregnancy cycle is used as a label to obtain the first model through training. The first model can be a classification model in machine learning, and this application does not limit the specific model architecture.

[0019] In combination with the first aspect and the above-mentioned implementation methods, in some implementation methods of the first aspect, obtaining a prediction result of the mental health status of the next pregnancy cycle includes: obtaining a second feature, the second feature including at least one of the following: heart rate variability in the current pregnancy cycle, sleep duration in the current pregnancy cycle, light exposure duration in the current pregnancy cycle, and air pressure changes in the current pregnancy cycle; determining a prediction result of the mental health status of the next pregnancy cycle based on the second feature and the second model, and the second model is used to predict the mental health status of the next pregnancy cycle.

[0020] It can be understood that sleep duration, light duration, air pressure changes, etc. will have an impact on the user's psychological state. Sufficient sleep and light, as well as high-pressure weather (mostly sunny days) will have a positive psychological impact on the user. When the user is in a positive psychological state (such as happiness, relaxation and satisfaction), the blood pressure can be maintained at a normal level. The present application can predict the user's mental health state in the next pregnancy cycle through characteristics such as heart rate variability, sleep duration, light duration, and air pressure changes, wherein the sleep duration of the current pregnancy cycle can be the average duration of multiple sleep durations obtained in the current pregnancy cycle, or it can be the shortest sleep duration among the multiple sleep durations obtained in the current pregnancy cycle. The light duration of the current pregnancy cycle can be the average duration of multiple light durations obtained in the current pregnancy cycle, and the air pressure change of the current pregnancy cycle can be the average of multiple air pressure values ​​obtained in the current pregnancy cycle.

[0021] In combination with the first aspect and the above-mentioned implementation methods, in some implementation methods of the first aspect, obtaining a prediction result of the blood pressure fluctuation state in the next pregnancy cycle includes: obtaining a third feature, the third feature including at least one of the following: the user's age, the user's current pregnancy cycle, the current pregnancy cycle body mass index and the previous pregnancy cycle body mass index, the user's blood pressure in the previous pregnancy cycle, and the waveform characteristics of the photoplethysmogram; determining the prediction result of the blood pressure fluctuation state in the next pregnancy cycle based on the third feature and the third model, and the third model is used to predict the blood pressure fluctuation state in the next pregnancy cycle.

[0022] In a second aspect, an embodiment of the present application provides an electronic device, comprising: one or more processors; one or more memories; the memory stores one or more programs, and when one or more programs are executed by the processor, the electronic device executes any method described in any one of the above-mentioned first aspects.

[0023] In a third aspect, an embodiment of the present application provides a device, which is included in an electronic device, and the device has the function of realizing the above-mentioned aspects and the behavior of the electronic device in the possible implementation methods of the above-mentioned aspects. The function can be implemented by hardware, or the corresponding software can be implemented by hardware. The hardware or software includes one or more modules or units corresponding to the above-mentioned functions. For example, a display module or unit, a detection module or unit, a processing module or unit, etc.

[0024] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, wherein instructions are stored in the computer-readable storage medium, and when the computer-readable storage medium is run on a computer, the computer executes the method described in the first aspect above.

[0025] In a fifth aspect, an embodiment of the present application provides a computer program product comprising instructions, which, when executed on a computer, enables the computer to execute the method described in the first aspect above.

[0026] The technical effects obtained by the above-mentioned second, third, fourth and fifth aspects are similar to the technical effects obtained by the corresponding technical means in the above-mentioned first aspect, and will not be repeated here. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] Figure 1 A schematic diagram of an application scenario provided by an embodiment of the present application is shown;

[0028] Figure 2 A schematic diagram of a user interface provided in an embodiment of the present application is shown;

[0029] Figure 3 A schematic diagram showing a display of an evaluation result provided in an embodiment of the present application is shown;

[0030] Figure 4 A schematic diagram showing another example of evaluation result display provided in an embodiment of the present application is shown;

[0031] Figure 5 A schematic diagram showing another example of evaluation result display provided in an embodiment of the present application is shown;

[0032] Figure 6 A schematic diagram of a user interface provided in an embodiment of the present application is shown;

[0033] Figure 7 A schematic diagram of a process for assessing blood pressure risk during pregnancy provided in an embodiment of the present application is shown;

[0034] Figure 8 A schematic diagram of a multi-wavelength PPG signal provided in an embodiment of the present application is shown;

[0035] Fig. 9 A schematic diagram showing another example of a PPG signal provided in an embodiment of the present application is shown;

[0036] Fig.10 A schematic diagram showing another example of a PPG signal provided in an embodiment of the present application is shown;

[0037] Fig.11 A schematic diagram of a risk quantification curve provided in an embodiment of the present application is shown;

[0038] Fig.12 A schematic diagram of the hardware structure of an electronic device provided in an embodiment of the present application is shown;

[0039] Fig.13 A software structure block diagram of an electronic device provided in an embodiment of the present application is shown;

[0040] Fig.14 A schematic diagram of the structure of a device provided in an embodiment of the present application is shown;

[0041] Fig.15 A schematic structural diagram of a chip provided in an embodiment of the present application is shown. DETAILED DESCRIPTION

[0042] In order to make the purpose, technical scheme and advantages of the present application clearer, the implementation mode of the present application will be further described in detail below with reference to the accompanying drawings. Hereinafter, the terms "first" and "second" are used for descriptive purposes only and cannot be understood as indicating or implying relative importance or implicitly indicating the number of indicated technical features. Thus, the features defined as "first" and "second" may explicitly or implicitly include one or more of the features. In the description of the present embodiment, unless otherwise specified, the meaning of "multiple" is two or more.

[0043] Gestational hypertension refers to a group of diseases in which pregnancy and high blood pressure coexist. It is a common obstetric disease. The clinical manifestations of gestational hypertension are diverse, including high blood pressure, proteinuria, edema, and multiple organ damage throughout the body. In severe cases, convulsions (eclampsia) and coma may occur. Gestational hypertension seriously affects the health of mother and baby and is one of the main causes of maternal and perinatal mortality.

[0044] Currently, the main way to check whether a pregnant woman suffers from gestational hypertension is to measure blood pressure with instruments, but it is difficult to assess in advance whether there is a risk of blood pressure during pregnancy through electronic devices carried by the user.

[0045] To this end, the present application provides a method for risk assessment of blood pressure during pregnancy, in which the electronic device can obtain the prediction results of the blood circulation state, mental health state, and blood pressure fluctuation state of the next pregnancy cycle in the current pregnancy cycle; determine the risk assessment score of the blood pressure in the next pregnancy cycle according to the prediction results of the blood circulation state, mental health state, and blood pressure fluctuation state; when the risk assessment score is in the first interval, determine the risk level of the blood pressure in the next pregnancy cycle as a risk-free level; when the risk assessment score is in the second interval, determine the risk level of the blood pressure in the next pregnancy cycle as a risky level. Based on the above technical solution, the electronic device can implement risk prediction and assessment of the blood pressure state of the next pregnancy cycle in the current pregnancy cycle, and can remind the user to seek medical treatment in time when the blood pressure risk level of the next pregnancy cycle is risky, which helps the user pay attention to their own health and prevent high blood pressure during pregnancy, thereby preventing pregnancy-specific diseases such as hypertension, preeclampsia, eclampsia, chronic hypertension complicated with preeclampsia, and chronic hypertension.

[0046] The method provided in the embodiment of the present application is applied to an electronic device 100, which may be, but not limited to, a mobile phone, a wearable device, a tablet computer, a laptop computer, a handheld computer, a notebook computer, a super mobile personal computer, etc. The wearable device may be, but not limited to, a smart watch, a smart bracelet, smart glasses, etc. The embodiment of the present application does not limit this.

[0047] The electronic device 100 includes a variety of sensors, such as a photoplethysmography (PPG) sensor, a light sensor, an air pressure sensor, a weight scale, an acceleration sensor, etc. The PPG sensor is used to collect PPG signals, the light sensor is used to collect light duration, the air pressure sensor is used to obtain air pressure values, and the weight scale is used to obtain the weight of the user. Through a variety of sensors, the electronic device 100 can obtain a variety of features reflecting the blood circulation state, mental health state, and blood pressure fluctuation state in the current pregnancy cycle. The multiple features may include PPG features, sleep duration, body mass index, light duration, air pressure changes, etc. Furthermore, the electronic device 100 can predict the user's blood circulation state, mental health state, and blood pressure fluctuation state in the next pregnancy cycle based on the multiple features of the current pregnancy cycle obtained, and evaluate the user's blood pressure risk in the next pregnancy cycle. In some embodiments, the electronic device 100 can use more or fewer sensors to obtain multiple features corresponding to the current pregnancy cycle.

[0048] In some implementations, the electronic device 100 may obtain multiple features corresponding to the current pregnancy cycle from the electronic device 200. The electronic device 200 may be a mobile phone, a wearable device, a tablet computer, a laptop computer, etc. This embodiment of the application is not limited to this.

[0049] For example, Figure 1 This is a schematic diagram of an application scenario of a method for assessing blood pressure risk during pregnancy provided in an embodiment of the present application. Figure 1 , the electronic device 100 may be a mobile phone, and the electronic device 200 may be a smart bracelet worn on the wrist of the user. The electronic device 100 and the electronic device 200 may have a binding relationship. Among them, the electronic device 100 and the electronic device 200 can be bound by logging into the same account (for example, a Honor account). Alternatively, the electronic device 100 and the electronic device 200 can be bound by Bluetooth pairing. The embodiment of the present application does not limit the method for establishing a binding relationship between the electronic device 100 and the electronic device 200.

[0050] The electronic device 200 may include a PPG sensor, and the electronic device 200 may collect PPG signals through the PPG sensor, extract PPG features from the PPG signals, and send the PPG signals or PPG features to the electronic device 100. The electronic device 100 receives the PPG signal or PPG features from the electronic device 200, and predicts the blood circulation state, mental health state, and blood pressure fluctuation state of the user in the next pregnancy cycle based on the PPG features from the electronic device 200 and other features acquired by the electronic device 100 itself, thereby evaluating the blood pressure risk of the user in the next pregnancy cycle. It should be understood that the electronic device 200 may also use more or fewer sensors to acquire other features.

[0051] In other implementations, the electronic device 200 may predict at least one of the blood circulation state, mental health state, and blood pressure fluctuation state in the next pregnancy cycle based on multiple characteristics of the current pregnancy cycle, and send the prediction result to the electronic device 100. The electronic device 100 may evaluate the blood pressure risk of the user in the next pregnancy cycle based on the prediction result obtained from the electronic device 200 and the prediction result determined by itself.

[0052] In an embodiment of the present application, every 7 days during the pregnancy period can be regarded as a pregnancy cycle. For example, the current pregnancy cycle may be the 5th week of the user's pregnancy, and the next pregnancy cycle may be the 6th week of the user's pregnancy. Every day during the user's pregnancy period can also be regarded as a pregnancy cycle, which is not limited in the present application. The electronic device 100 can automatically evaluate the level of the user's blood pressure risk in the next pregnancy cycle every preset time period (such as 24 hours). The user can also manually trigger the electronic device 100 to perform a blood pressure risk assessment, and the electronic device 100 can save the obtained assessment results. The embodiment of the present application does not limit the length of the above-mentioned preset time period.

[0053] In the embodiment of the present application, the risk of blood pressure during pregnancy refers to the risk of high blood pressure during pregnancy, which may lead to hypertension. The higher the blood pressure risk level of the next pregnancy cycle, the greater the risk of high blood pressure in the next pregnancy cycle, and the more likely it is to develop hypertension during pregnancy.

[0054] Taking the electronic device 100 as a mobile phone as an example, some user interface schematic diagrams involved in the pregnancy blood pressure risk assessment method provided in this application are introduced below.

[0055] Figure 2 The schematic diagram exemplarily shows the process of a user triggering a mobile phone to enter a user interface for pregnancy blood pressure risk assessment.

[0056] Figure 2 (a) in FIG. 1 is a schematic diagram of the home screen interface of a mobile phone. The home screen interface may include an application icon display area for displaying various types of application (App) icons, such as a clock icon, a calendar icon, a gallery icon, a memo icon, a file management icon, an email icon, a music icon, a calculator icon, a video icon, a sports and health icon, a weather icon, a browser icon, a smart life icon, a setting icon, a recorder icon, an App Store icon, a camera icon, a contact book icon, a phone icon, a message icon, etc.

[0057] The mobile phone can receive a user's click operation on the sports health APP icon. In response to the user's click operation on the sports health APP icon, the mobile phone can start the sports health APP and display the following information: Figure 2 The main interface of the sports health app shown in (b) in the figure displays multiple function cards such as "blood pressure", "sleep", and "blood pressure risk during pregnancy". The user can click on the "blood pressure risk during pregnancy" card, and the mobile phone can enter the following functions in response to the user's click on the "blood pressure risk assessment during pregnancy" card: Figure 2 The interface shown in (c) or (d) in the figure may display the evaluation result of the electronic device on the blood pressure risk level of the next pregnancy cycle. Figure 2 As shown in (c) in FIG. 1 , when the blood pressure risk level of the next pregnancy cycle is determined to be a risk-free level, “risk-free” may be displayed to the user; Figure 2 As shown in (d), when the assessment result of the blood pressure risk level for the next pregnancy cycle is determined to be a risky level, "risky" can be displayed to the user. In addition, according to the assessed risk level, the mobile phone can display relevant suggestions / tips on the user interface. For example, in the case of "no risk", the prompt suggestion can be displayed as "basically no risk, please continue to maintain a healthy state", and in the case of "risky", the prompt suggestion can be displayed as "there is a risk of elevated blood pressure, please pay attention in time". The specific content of the above-mentioned prompt suggestions in the embodiment of the present application is not limited.

[0058] In such Figure 2 The interfaces shown in (c) and (d) may also display the current week of pregnancy and a "start evaluation" control. The user may click on the "start evaluation" control, and in response to the user's click operation, the mobile phone may re-evaluate the user's blood pressure risk level in the next pregnancy cycle.

[0059] In some implementations, the pregnancy blood pressure risk assessment function can also be turned on and displayed in other function cards.

[0060] Figure 3 Another schematic diagram of the display of the result of the blood pressure risk level assessment during pregnancy provided by the embodiment of the present application is shown, wherein the risk level can be further divided into a low risk level, a medium risk level and a high risk level. Figure 3 As shown in (a) in FIG. 1 , when the blood pressure risk level of the next pregnancy cycle is assessed as a risk-free level, “risk-free” may be displayed to the user, and accordingly, the prompt may be displayed as “basically risk-free, please continue to maintain a healthy state”; Figure 3 As shown in (b) in FIG. 1 , when the blood pressure risk level of the next pregnancy cycle is assessed as a low risk level, “low risk” may be displayed to the user, and accordingly, the prompt may be displayed as “there is a risk of elevated blood pressure, please pay attention to your mentality or sleep problems”; Figure 3As shown in (c) in FIG. 1 , when the blood pressure risk level of the next pregnancy cycle is assessed as a medium risk level, “medium risk” may be displayed to the user, and accordingly, the prompt may be displayed as “there is a risk of elevated blood pressure, please pay attention to issues such as mentality, sleep, and blood pressure, and seek medical advice in a timely manner”; Figure 3 As shown in (d), when the assessment result of the blood pressure risk level for the next pregnancy cycle is a high risk level, "high risk" can be displayed to the user, and correspondingly, the prompt suggestion can be displayed as "The risk of increased blood pressure is high, please find a professional doctor for diagnosis as soon as possible." By further dividing the risk level into a low risk level, a medium risk level, and a high risk level, users can understand their own health conditions more clearly through the risk level, which can improve the user experience. It should be understood that the embodiment of the present application exemplarily divides the risk level into a low risk level, a medium risk level, and a high risk level. In other embodiments, the risk level can also be divided into fewer or more levels, for example, into a low risk level and a high risk level.

[0061] In some implementations, see Figure 4 The mobile phone can draw a three-dimensional risk radar map of pregnancy based on the predicted results of blood circulation status, mental health status, and blood pressure fluctuation status in the next pregnancy cycle. Figure 4 As shown in (a) of FIG. 1 , in the user interface that displays the risk level and prompt information, a "view details" control can also be displayed. The user can click "view details", and in response to the user's click operation, the mobile phone can enter the following Figure 4 The interface shown in (b) in the figure can display the three-dimensional risk radar chart 41 of pregnancy and the prediction results corresponding to the blood circulation status, mental health status, and blood pressure fluctuation status. The radar chart 41 is composed of multiple concentric circles, and the radii of the concentric circles are 0.2, 0.4, 0.6, 0.8, and 1.0 respectively. The distances from the points M, C, and L on the circles to the center of the circles respectively represent the health levels of the blood pressure fluctuation status, mental health status, and blood circulation status. From 0.2 to 1.0, the health level gradually decreases. In the embodiment of the present application, the area of ​​the triangle LCM formed by the points on the circle can represent the risk level. The area S of the triangle LCM LCM The larger the number, the higher the risk level. The embodiment of the present application can enable the user to more clearly and intuitively understand the factors that lead to the risk by displaying detailed information, so as to adjust the user's own status in a timely and targeted manner.

[0062] In some implementations, the mobile phone may display the determined blood pressure risk level for the next pregnancy cycle on the lock screen or the negative one screen to remind the user whether there is a risk.

[0063] In some implementations, see Figure 5 , Figure 5is another schematic diagram showing the results of the pregnancy blood pressure risk level assessment provided by the embodiment of the present application, such as Figure 5 As shown in (a) in the figure, in the case of medium risk and high risk, the mobile phone can send a warning message to remind the user, for example, the warning message can be "It is monitored that you have a greater risk of high blood pressure in the next pregnancy cycle, please seek medical advice in time." Figure 5 As shown in (b) in the figure, the mobile phone can remind the user of the risk level of blood pressure during pregnancy through voice. For example, in the case of high risk, the voice message sent by the mobile phone is "The risk of high blood pressure is high, please find a professional doctor for diagnosis as soon as possible." Through the above implementation method, users can receive risk information in a timely manner.

[0064] In some implementations, in high-risk situations, the mobile phone can automatically contact pre-set emergency contacts, such as sending text messages or voice messages, to ensure that the user can receive timely medical treatment.

[0065] Figure 6 is a user interface diagram provided in an embodiment of the present application. Figure 6 When using the pregnancy blood pressure risk assessment function, after clicking the "pregnancy blood pressure risk" card, the phone can also display the following information: Figure 6 In the personal information filling interface shown in (b) of FIG. 1 , the user can fill in the nickname, age, height, weight, current pregnancy period, emergency contact, etc., so that the mobile phone can save the user's personal information. In some implementations, the user can also fill in or modify personal information in "My"-"Personal Information".

[0066] In some implementations, the mobile phone assesses the user's blood pressure risk level in the next pregnancy cycle. After obtaining the assessment result, the assessment result can be sent to the smart bracelet, and the smart bracelet can display the assessment result, such as "Your blood pressure risk level has been assessed, please check the assessment result on your mobile phone."

[0067] It should be understood that the above user interface is an exemplary description of the embodiment of the present application and should not constitute a limitation on the present application.

[0068] In short, the above user interface can display the user's blood pressure risk assessment results for the next pregnancy cycle, and the user can view the future blood pressure risk level. The user can refer to the above risk assessment results to adjust his or her mood and lifestyle, etc., to reduce the possible risk of increased blood pressure.

[0069] The method provided in the embodiment of the present application is described in detail below. Figure 7It is a flowchart of a method for assessing blood pressure risk during pregnancy provided in an embodiment of the present application. The method is executed by the electronic device 100 and may specifically include the following steps S701-S709.

[0070] S701, obtaining a first feature of a photoplethysmogram (PPG) signal in a current pregnancy cycle.

[0071] The electronic device 100 can collect PPG signals in real time through a PPG sensor, or can obtain PPG signals collected in the current pregnancy cycle from a memory. Alternatively, the electronic device 100 can obtain PPG signals in the current pregnancy cycle from an electronic device 200 (such as a smart bracelet).

[0072] Among them, the PPG sensor includes a light transmitter and a light receiver, and the light transmitter can transmit a light signal to the skin surface. The light signal emitted can be absorbed, reflected and scattered by blood, skin, muscle, bone and other tissues in the blood vessels. The light receiver can receive the reflected or scattered light signal. The volume of blood in the blood vessels will change during the contraction and relaxation of the heart, and the light signal absorbed by the blood in the blood vessels will also change. The intensity of the light signal received by the light receiver will also change with the contraction and relaxation of the heart. The electronic device 100 can generate a PPG signal based on the light signal received by the light receiver. The light signal emitted by the light transmitter may include light of different wavelengths, such as infrared light, red light, and green light. Therefore, the PPG signal can be a multi-wavelength PPG (Multi-wave Photoplethysmograph, MWPPG) signal.

[0073] The heart contracts and relaxes regularly to maintain the normal operation of blood circulation. Blood pressure is the lateral pressure exerted on the blood vessel wall per unit area when blood flows in the blood vessels. In normal pregnancy, the blood volume in the pregnant woman's body increases, and the heart needs more blood to meet the needs of the fetus and uterus. In order to adapt to this demand, the pregnant woman's heart will increase and the amount of blood pumped by the heart will also increase. However, in the case of gestational hypertension, the increase in the pregnant woman's blood pressure may cause disorders in the blood circulation system, which may include vasospasm and vascular damage, which restricts blood flow. Therefore, the occurrence of gestational hypertension is closely related to changes in the blood circulation system in pregnant women. The blood circulation status can effectively reflect whether the user's blood pressure is at risk of increase.

[0074] In the embodiment of the present application, the blood circulation state can be judged by the contraction characteristics of the blood vessels and / or the blood volume characteristics. Specifically, when the heart contracts, the blood flows from the heart to the peripheral blood vessels; when the heart relaxes, the blood continues to flow forward and is affected by the resistance that hinders the blood flow through the blood vessels; the forward wave generated by the forward flow of blood and the reflected wave generated by the resistance of the blood vessels to the blood flow are mixed to produce the pulse of the peripheral blood vessels. Correspondingly, the PPG signal is a mixture of the forward wave and the reflected wave, and the waveform of the PPG signal consists of an ascending branch and a descending branch. The blood vessels are elastic cavities. The contraction of the blood vessels during the contraction and relaxation of the heart can significantly change the caliber of the blood vessels, thereby changing the resistance to blood flow. In addition, the change in blood volume (blood volume) can change the resistance of the peripheral blood vessels. The power of the blood flowing forward and the resistance of the blood vessels to the blood flow affect the propagation speed of the blood flow in the blood vessels, and then affect the speed of the pulse wave rising and falling, thereby affecting the amplitude difference, slope, area under the curve and time interval of the rising branch and the descending branch of the PPG signal waveform.

[0075] The electronic device 100 can extract a first feature characterizing the contraction characteristics of the blood vessels and / or the blood volume characteristics from the PPG signal, and analyze whether the state of blood circulation is normal through the first feature. The contraction characteristics of the blood vessels can be characterized by the arteriolar pulse transit time (PPT), and correspondingly, the first feature can include the peak transit time MWPTT_R of the multi-wavelength PPG and the maximum rise speed transit time MWPTT_V of the multi-wavelength PPG. The blood volume characteristics can be characterized by the waveform characteristics of the PPG signal corresponding to the green light, and correspondingly, the first feature can include the time interval between the pulse wave peak and the dicrotic wave trough, the pulse wave amplitude ratio, the peak-to-trough amplitude ratio, etc.

[0076] Figure 8A schematic diagram of a multi-wavelength PPG signal provided by an embodiment of the present application is shown, wherein from top to bottom are the waveforms of the PPG signal obtained by green light, red light and infrared light, respectively. In the figure, R1 is the peak point corresponding to infrared light in the first cardiac cycle, R2 is the peak point corresponding to green light in the second cardiac cycle, V1 is the maximum rising speed point corresponding to infrared light in the second cardiac cycle, and V2 is the maximum rising speed point corresponding to green light in the third cardiac cycle. A cardiac cycle refers to the time from the start of one heartbeat to the start of the next heartbeat. Each contraction and relaxation of the heart constitutes a cardiac cycle, that is, the time interval between the starting point of the pulse wave and the trough point of the pulse wave. The first cardiac cycle is adjacent to the second cardiac cycle, and the second cardiac cycle is adjacent to the third cardiac cycle. The peak transfer time MWPTT_R of the multi-wavelength PPG can be the time interval between the moment corresponding to R1 and the moment corresponding to R2, that is, the peak transfer time between different wavelengths in two adjacent cardiac cycles. The maximum rise rate transfer time MWPTT_V of the multi-wavelength PPG may be the time interval between the moment corresponding to V1 and the moment corresponding to V2, that is, the maximum rise rate transfer time between different wavelengths in two adjacent cardiac cycles. In some implementations, MWPTT_R may also be the time interval between the peak corresponding to the infrared light and the peak corresponding to the green light in the same cardiac cycle, and MWPTT_V may also be the time interval between the maximum rise rate point corresponding to the infrared light and the maximum rise rate point corresponding to the green light in the same cardiac cycle.

[0077] Fig. 9 is the waveform of the PPG signal obtained by green light in one cardiac cycle, where S0 is the amplitude of the pulse wave starting point, P0 is the amplitude of the pulse wave peak point, and E0 is the amplitude of the pulse wave trough point. The pulse wave amplitude ratio (photoplethysmogram intensity ratio, PIR) is the ratio of the peak point amplitude to the starting point amplitude, that is, PIR = P0 / S0. The peak-to-valley amplitude ratio (ratio of maximum peak intensity to valley intensity, RIPV) is the ratio of the peak amplitude to the trough amplitude, that is, PIR = P0 / E0. The time interval between the pulse wave peak and the dicrotic wave trough is also the reciprocal of the large artery stiffness index (LASI) 1 / LASI.

[0078] S702: Determine a prediction result of the blood circulation state in the next pregnancy cycle based on the first feature and the first model.

[0079] After the electronic device 100 obtains the first feature (MWPTT_R, MWPTT_V, 1 / LASI, PIR, PIR, etc.) in the current pregnancy cycle, it inputs the first feature into the first model for classification, and outputs the prediction result of the blood circulation state in the next pregnancy cycle through the first model. The blood circulation state in the next pregnancy cycle can be one of the four categories of mild, moderate, moderately severe, and severe. Among them, mild means that the blood circulation state is in normal condition, severe means that the blood circulation state may be abnormal, and the lighter the degree (i.e., from severe to mild), the more normal the blood circulation state.

[0080] In the embodiment of the present application, the first model can be obtained by pre-training. Specifically, the first feature data such as MWPTT_R, MWPTT_V, 1 / LASI, PIR, PIR, etc. of multiple pregnant users in each pregnancy cycle can be obtained through big data, and then the feature data of the previous pregnancy cycle in two adjacent pregnancy cycles is used as input, and the feature data of the next pregnancy cycle is used as a label to obtain the first model through training. The first model can be a classification model in machine learning, and the specific model architecture is not limited in this application.

[0081] S703, obtaining a second feature, the second feature including but not limited to heart rate variability in the current pregnancy cycle, sleep duration in the current pregnancy cycle, light exposure duration in the current pregnancy cycle, and air pressure changes in the current pregnancy cycle.

[0082] In addition to predicting the user's blood circulation status in the next pregnancy cycle, the electronic device 100 can also obtain a second feature reflecting the psychological health of pregnancy in the current pregnancy cycle, and predict the user's psychological health status in the next pregnancy cycle through the second feature. It can be understood that sleep duration, light duration, air pressure changes, etc. will affect the user's psychological state. Sufficient sleep and light, as well as high-pressure weather (mostly sunny days) will bring positive psychological effects to the user. When the user is in a positive psychological state (such as happiness, relaxation, and satisfaction), blood pressure can be maintained at a normal level.

[0083] Among them, heart rate variability (HRV) refers to the change in the difference between successive heartbeat cycles, which can reflect the user's psychological state. Heart rate variability can be monitored by a PPG sensor. Sleep duration can be monitored by a PPG sensor and an acceleration sensor, etc., light duration can be monitored by a light sensor, a camera, etc., and air pressure changes can be monitored by an air pressure sensor. The electronic device 100 can calculate the heart rate variability, sleep duration, light duration, and air pressure according to the preset time intervals corresponding to the heart rate variability, sleep duration, light duration, and air pressure, and obtain multiple heart rate variabilities, multiple sleep durations, multiple light durations, and multiple air pressures within the pregnancy cycle. The specific measurement method is not limited in this application. For example, if the pregnancy cycle is 7 days, the preset time intervals corresponding to the heart rate variability, sleep duration, light duration, and air pressure can be 30 minutes, 24 hours, 12 hours, and 5 hours, respectively, that is, the heart rate variability is measured every 30 minutes.

[0084] The sleep duration of the current pregnancy cycle may be the average duration of multiple sleep durations obtained in the current pregnancy cycle, or may be the shortest sleep duration among the multiple sleep durations obtained in the current pregnancy cycle. The light duration of the current pregnancy cycle may be the average duration of multiple light durations obtained in the current pregnancy cycle, and the air pressure change of the current pregnancy cycle may be the average value of multiple air pressure values ​​obtained in the current pregnancy cycle.

[0085] S704: Determine a prediction result of the mental health status of the next pregnancy cycle based on the second feature and the second model.

[0086] After the electronic device 100 obtains the second feature in the current pregnancy cycle, it inputs the second feature into the second model, and outputs the prediction result of the mental health state in the next pregnancy cycle through the second model. The mental health state in the next pregnancy cycle can be one of the four categories of good, general, poor, and extremely poor. The better the mental health state, the healthier the user is.

[0087] In the embodiment of the present application, the second model can be obtained by pre-training. Specifically, multiple users in pregnancy can be obtained through big data, and the above-mentioned second feature data corresponding to the user in each pregnancy cycle can be obtained. Then, the second feature data of the previous pregnancy cycle of two adjacent pregnancy cycles is used as input, and the second feature data of the next pregnancy cycle is used as a label to obtain the second model through training. The second model can be a classification model in machine learning, and the specific model architecture is not limited in this application.

[0088] In some implementations, the electronic device can save the second characteristic data obtained in each pregnancy cycle. In the current pregnancy cycle (at least the third week), the electronic device can obtain the data of the previous pregnancy cycle, use the second characteristic data of the previous pregnancy cycle of two adjacent pregnancy cycles as input, and use the second characteristic data of the next pregnancy cycle as a label to obtain the second model through training. Similarly, the above-mentioned first model and subsequent third model can also be trained in real time through the user's own data.

[0089] S705, obtaining a third feature, which includes but is not limited to the user's age, current pregnancy period, change in body mass index from the previous pregnancy period to the current pregnancy period, blood pressure in the previous pregnancy period, and waveform characteristics of the photoplethysmogram.

[0090] It should be understood that different physiological information such as age, height, and weight will cause different changes in users' blood pressure, and changes in blood pressure will also affect the amplitude difference, slope, area under the curve, and time interval of the rising and falling branches of the PPG signal waveform.

[0091] The electronic device 100 can also obtain a third feature reflecting the blood pressure fluctuation during pregnancy in the current pregnancy cycle, and predict the blood pressure fluctuation state of the user in the next pregnancy cycle through the third feature. Among them, the body mass index (BMI) is calculated by dividing the weight (kg) by the square of the height (m). The user's weight can be measured by a weight scale installed in the electronic device 100, or obtained by a weight scale associated with the electronic device 100. The user's height and age can be obtained through the personal information filled in by the user. The change in body mass index from the previous pregnancy cycle to the current pregnancy cycle (abbreviated as the month-on-month BMI change, R BMI ) can be calculated by formula (1).

[0092]

[0093] Wherein BMI0 is the body mass index of the previous pregnancy cycle, BMI1 is the body mass index of the current pregnancy cycle, and HP is the cycle number of the current pregnancy cycle. For example, if the current pregnancy cycle is the 5th week of the user's pregnancy, then HP=5.

[0094] The electronic device 100 can measure blood pressure every certain time (such as 30 minutes), and the blood pressure of the last pregnancy cycle can be the average of multiple blood pressures measured within 7 days. The third feature can also include the blood pressure of the current pregnancy cycle, and the blood pressure of the current pregnancy cycle can be the average of multiple blood pressures measured in the current pregnancy cycle.

[0095] The waveform characteristics of the photoplethysmogram may be the waveform characteristics of the PPG signal acquired by green light, and the waveform characteristics may include the pulsation period Ht (also called cardiac cycle), rising area A0, maximum rising speed As0, diastolic area S4, PIR, RIPV, etc. Fig.10 As shown in the figure, the rising area A0 is the area under the curve from the pulse wave starting point (marked as a) to the dicrotic wave trough point (marked as b), the diastolic area S4 is the area under the curve from the dicrotic wave peak point (marked as c) to the next pulse wave starting point (marked as f), and the maximum rising speed As0 is the maximum slope of the rising branch of the pulse wave. It should be noted that the pulsation period H t (also known as cardiac cycle), rising area A0, maximum rising speed As0, and diastolic area S4 can also be used as the first feature to calculate the above-mentioned blood circulation state.

[0096] S706: Determine a prediction result of the blood pressure fluctuation state in the next pregnancy cycle based on the third feature and the third model.

[0097] After obtaining the third feature, the third feature can be input into the third model, and the prediction result of the blood pressure fluctuation state in the next pregnancy cycle can be output through the third model. The blood pressure fluctuation state in the next pregnancy cycle refers to the range of blood pressure fluctuation in the next pregnancy cycle obtained by comparing with the current pregnancy cycle, or the magnitude of the blood pressure fluctuation. For example, the blood pressure fluctuation state can be divided into four categories according to the fluctuation range (absolute value): the fluctuation range is less than 2 mmHg, the fluctuation range is greater than or equal to 2 mmHg and less than 10 mmHg, the fluctuation range is greater than or equal to 10 mmHg and less than 15 mmHg, and the fluctuation range is greater than 20 mmHg.

[0098] In the embodiment of the present application, the third model can be pre-trained. Specifically, multiple users in pregnancy can be obtained through big data, and the third characteristic data corresponding to the user in each pregnancy cycle can be obtained. Then, the third characteristic data of the first pregnancy cycle of two adjacent pregnancy cycles is used as input, and the third characteristic data of the second pregnancy cycle is used as a label to obtain the third model through training. The third model can be a classification model in machine learning, and the specific model architecture is not limited in this application.

[0099] In summary, through the above steps S701 to S706, the electronic device 100 can obtain the prediction results of the blood circulation state, mental health state, and blood pressure fluctuation state in the next pregnancy cycle in the current pregnancy cycle. It should be noted that the application does not limit the order of obtaining the prediction results of the blood circulation state, mental health state, and blood pressure fluctuation state.

[0100] S707, determining a risk assessment score for blood pressure in the next pregnancy cycle based on the predicted results of blood circulation status, mental health status, and blood pressure fluctuation status.

[0101] After determining the prediction results corresponding to the blood circulation state, mental health state, and blood pressure fluctuation state of the next pregnancy cycle, the electronic device 100 can determine the numerical values ​​(also called risk evaluation coefficients) corresponding to the prediction results of the blood circulation state, mental health state, and blood pressure fluctuation state, respectively, and the numerical values ​​are used to measure the risk levels of different prediction results; according to the numerical values ​​r corresponding to the prediction results of the blood circulation state, mental health state, and blood pressure fluctuation state, respectively L 、r C 、r M , determine the blood pressure risk assessment score for the next pregnancy cycle.

[0102] Exemplarily, referring to Table 1, when the prediction result of the blood circulation state is mild, the corresponding value is 0.1, when the prediction result of the blood circulation state is moderate, the corresponding value is 0.6, when the prediction result of the blood circulation state is moderate to severe, the corresponding value is 0.8, and when the prediction result of the blood circulation state is severe, the corresponding value is 1. When the prediction result of the mental health state is good, the corresponding value is 0.1, when the prediction result of the mental health state is general, the corresponding value is 0.2, when the prediction result of the mental health state is poor, the corresponding value is 0.6, and when the prediction result of the mental health state is extremely poor, the corresponding value is 1. When the predicted result of the blood pressure fluctuation state is that the fluctuation range is less than 2 mmHg, the corresponding value is 0.1; when the predicted result of the blood pressure fluctuation state is that the fluctuation range is greater than or equal to 2 mmHg and less than 10 mmHg, the corresponding value is 0.2; when the predicted result of the blood pressure fluctuation state is that the fluctuation range is greater than or equal to 10 mmHg and less than 15 mmHg, the corresponding value is 0.5; when the predicted result of the blood pressure fluctuation state is that the fluctuation range is greater than 20 mmHg, the corresponding value is 1. The above values ​​are empirical results obtained through training with a large amount of data.

[0103] Table 1 The corresponding values ​​of different prediction results

[0104] <![CDATA[Blood circulation state (r L )]]> <![CDATA[Mental health status (r C )]]> <![CDATA[Blood pressure fluctuation state (r M )]]> Mild (0.1) Good (0.1) Fluctuation <2 mmHg (0.1) Moderate (0.6) Normal (0.2) 2mmHg≥ Fluctuation<10mmHg(0.2) Moderate to severe (0.8) Poor (0.6) 10 mmHg ≥ Fluctuation < 15 mmHg (0.5) Severe (1) Extreme(1) Fluctuation >20 mmHg (1)

[0105] For example, the risk assessment score of blood pressure in the next pregnancy cycle can be determined according to the numerical values ​​corresponding to the prediction results and formula (2). Formula (2) is obtained based on the above-mentioned three-dimensional risk radar chart of pregnancy.

[0106]

[0107] S708: When the risk assessment score is in the first interval, determine the risk level of blood pressure in the next pregnancy cycle as a no-risk level.

[0108] S709: When the risk assessment score is in the second interval, determine the risk level of blood pressure in the next pregnancy cycle as a risky level.

[0109] According to the various possible situations corresponding to all the above prediction results, multiple risk assessment scores can be determined. Fig.11 The three-dimensional risk quantification curve for pregnancy is composed of multiple risk assessment scores. According to experience, the risk assessment score below 0.2367 can be classified as no risk level (negligible risk), and the risk assessment score above 0.2367 can be classified as risk level. Correspondingly, the first interval is [0, 0.2367) and the second interval is [0.2367, 1].

[0110] For example, when the prediction results of the blood circulation status, mental health status, and blood pressure fluctuation status of the next pregnancy cycle are severe, extremely poor, and fluctuation>20mmHg, the corresponding values ​​are r L =1, r C =1, r M =1, the risk assessment score S LCM =1, the blood pressure risk level in the next pregnancy cycle is at a risk level.

[0111] Further, according to the severity of the risk, the second interval may include non-overlapping third intervals, fourth intervals, and fifth intervals in sequence, and the risk levels may be divided into low risk, medium risk, and high risk. As shown in Table 2, when the risk assessment score is in the third interval [0.2367, 0.2867), the electronic device 100 may determine that the risk level of blood pressure in the next pregnancy cycle is a low risk level (first risk level); when the risk assessment score is in the fourth interval [0.2867, 0.43), the electronic device 100 may determine that the risk level of blood pressure in the next pregnancy cycle is a medium risk level (second risk level); when the risk assessment score is in the fifth interval [0.43, 1], the electronic device 100 may determine that the risk level of blood pressure in the next pregnancy cycle is a high risk level (third risk level).

[0112] The electronic device 100 can output prompt information corresponding to the first risk level, the second risk level, or the third risk level through an interface or voice according to the risk level of blood pressure in the next pregnancy cycle, as shown in Table 2 and the above Figures 3 to 5 It should be understood that the above risk level classification is an exemplary description of the embodiments of the present application and should not constitute a limitation to the present application.

[0113] Table 2 Different risk levels and corresponding prompt information

[0114]

[0115] In summary, the embodiment of the present application provides a method for assessing the risk of blood pressure during pregnancy. The electronic device can obtain the prediction results of the blood circulation state, mental health state, and blood pressure fluctuation state of the next pregnancy cycle in the current pregnancy cycle, and then determine the corresponding risk assessment coefficient according to the prediction results of the blood circulation state, mental health state, and blood pressure fluctuation state, and then determine the risk assessment score of the blood pressure in the next pregnancy cycle; according to the risk assessment score and the preset interval, determine the risk level of the blood pressure in the next pregnancy cycle. Based on the above technical scheme, the electronic device can realize the risk prediction and assessment of the blood pressure state of the next pregnancy cycle in the current pregnancy cycle, and can remind the user to seek medical treatment in time when the blood pressure risk level of the next pregnancy cycle is risky, which helps the user to pay attention to their own health and prevent the increase of blood pressure during pregnancy, thereby preventing pregnancy-specific diseases such as hypertension, preeclampsia, eclampsia, chronic hypertension complicated with preeclampsia and chronic hypertension. The above method evaluates the blood pressure risk level of the next pregnancy cycle through three factors: blood circulation state, mental health state, and blood pressure fluctuation state, which can avoid miscalculation caused by abnormal single factors, and can more accurately obtain the blood pressure risk level of the next pregnancy cycle.

[0116] Combined with the above Figures 1 to 11 , the method for assessing blood pressure risk during pregnancy provided by the embodiment of the present application is described, and the electronic device and device for executing the above method provided by the embodiment of the present application are described below. The hardware structure diagram of the electronic device 100 that can implement the method provided by the present application is introduced below. Exemplary, Fig.12 A hardware structure diagram of an electronic device 100 provided in an embodiment of the present application is shown.

[0117] The electronic device 100 may include a processor 110, an external memory interface 120, an internal memory 121, a universal serial bus (USB) interface 130, a charging management module 140, a power management module 141, a battery 142, an antenna 1, an antenna 2, a mobile communication module 150, a wireless communication module 160, an audio module 170, a speaker 170A, a receiver 170B, a microphone 170C, an earphone interface 170D, a sensor module 180, a button 190, a motor 191, an indicator 192, a camera 193, a display screen 194, and a subscriber identification module (SIM) card interface 195, etc. The sensor module 180 may include a pressure sensor 180A, a gyroscope sensor 180B, an air pressure sensor 180C, a magnetic sensor 180D, an acceleration sensor 180E, a distance sensor 180F, a proximity light sensor 180G, a fingerprint sensor 180H, a temperature sensor 180J, a touch sensor 180K, an ambient light sensor 180L, a bone conduction sensor 180M, etc.

[0118] It is to be understood that the structure illustrated in the embodiment of the present invention does not constitute a specific limitation on the electronic device 100. In other embodiments of the present application, the electronic device 100 may include more or fewer components than shown in the figure, or combine some components, or separate some components, or arrange the components differently. The components shown in the figure may be implemented in hardware, software, or a combination of software and hardware.

[0119] The processor 110 may include one or more processing units, for example, the processor 110 may include an application processor (AP), a modem processor, a graphics processor (GPU), an image signal processor (ISP), a controller, a video codec, a digital signal processor (DSP), a baseband processor, and / or a neural-network processing unit (NPU). The different processing units may be independent devices or integrated into one or more processors. The processor 110 may be configured to perform the above Figure 7 Various operations in method embodiments are described.

[0120] Among them, the controller can generate an operation control signal according to the instruction operation code and the timing signal to complete the control of instruction fetching and execution.

[0121] The processor 110 may also be provided with a memory for storing instructions and data. In some embodiments, the memory in the processor 110 is a cache memory. The memory may store instructions or data that the processor 110 has just used or cyclically used. If the processor 110 needs to use the instruction or data again, it may be directly called from the memory. This avoids repeated access, reduces the waiting time of the processor 110, and thus improves the efficiency of the system.

[0122] In some embodiments, the processor 110 may include one or more interfaces. The interface may include an inter-integrated circuit (I2C) interface, an inter-integrated circuit sound (I2S) interface, a pulse code modulation (PCM) interface, a universal asynchronous receiver / transmitter (UART) interface, a mobile industry processor interface (MIPI), a general-purpose input / output (GPIO) interface, a subscriber identity module (SIM) interface, and / or a universal serial bus (USB) interface, etc. It can be understood that the interface connection relationship between the modules illustrated in the embodiment of the present invention is only a schematic illustration and does not constitute a structural limitation of the electronic device 100. In other embodiments of the present application, the electronic device 100 may also adopt different interface connection methods in the above embodiments, or a combination of multiple interface connection methods.

[0123] The charging management module 140 is used to receive charging input from a charger. The charger can be a wireless charger or a wired charger. 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, and provides power to the processor 110, the internal memory 121, the display screen 194, the camera 193, and the wireless communication module 160.

[0124] The wireless communication function of the electronic device 100 can be implemented through the antenna 1, the antenna 2, the mobile communication module 150, the wireless communication module 160, the modem processor and the baseband processor.

[0125] The mobile communication module 150 can provide solutions for wireless communications including 2G / 3G / 4G / 5G, etc., applied to the electronic device 100. The mobile communication module 150 may include at least one filter, a switch, a power amplifier, a low noise amplifier (LNA), etc. The mobile communication module 150 can receive electromagnetic waves from the antenna 1, and filter, amplify, and process the received electromagnetic waves, and transmit them to the modulation and demodulation processor for demodulation. The mobile communication module 150 can also amplify the signal modulated by the modulation and demodulation processor, and convert it into electromagnetic waves for radiation through the antenna 1. In some embodiments, at least some of the functional modules of the mobile communication module 150 can be set in the processor 110. In some embodiments, at least some of the functional modules of the mobile communication module 150 can be set in the same device as at least some of the modules of the processor 110.

[0126] The modem processor may include a modulator and a demodulator. Among them, the modulator is used to modulate the low-frequency baseband signal to be sent into a medium-high frequency signal. The demodulator is used to demodulate the received electromagnetic wave signal into a low-frequency baseband signal. The demodulator then transmits the demodulated low-frequency baseband signal to the baseband processor for processing. After the low-frequency baseband signal is processed by the baseband processor, it is passed to the application processor. The application processor outputs a sound signal through an audio device (not limited to a speaker 170A, a receiver 170B, etc.), or displays an image or video through a display screen 194. In some embodiments, the modem processor may be an independent device. In other embodiments, the modem processor may be independent of the processor 110 and be set in the same device as the mobile communication module 150 or other functional modules.

[0127] The wireless communication module 160 can provide wireless communication solutions 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), etc., which are applied to the electronic device 100. The wireless communication module 160 can be one or more devices integrating at least one communication processing module. The wireless communication module 160 receives electromagnetic waves via the antenna 2, modulates the frequency of the electromagnetic wave signal and performs filtering, and sends the processed signal to the processor 110. The wireless communication module 160 can also receive the signal to be sent from the processor 110, modulate the frequency of it, amplify it, and convert it into electromagnetic waves for radiation through the antenna 2.

[0128] In some embodiments, the antenna 1 of the electronic device 100 is coupled to the mobile communication module 150, and the antenna 2 is coupled to the wireless communication module 160, so that the electronic device 100 can communicate with the network and other devices through wireless communication technology. The wireless communication technology may include global system for mobile communications (GSM), general packet radio service (GPRS), code division multiple access (CDMA), wideband code division multiple access (WCDMA), time-division code division multiple access (TD-SCDMA), long term evolution (LTE), BT, GNSS, WLAN, NFC, FM, and / or IR technology. The GNSS may include a global positioning system (GPS), a global navigation satellite system (GLONASS), a Beidou navigation satellite system (BDS), a quasi-zenith satellite system (QZSS) and / or a satellite based augmentation system (SBAS).

[0129] The electronic device 100 implements the display function through a GPU, a display screen 194, and an application processor. The GPU is a microprocessor for image processing, which is connected to the display screen 194 and the application processor. The GPU is used to perform mathematical and geometric calculations for graphics rendering. The processor 110 may include one or more GPUs that execute program instructions to generate or change display information. The display screen 194 is used to display images, videos, etc. The electronic device 100 can implement the shooting function through an ISP, a camera 193, a video codec, a GPU, a display screen 194, and an application processor.

[0130] NPU is a neural network (NN) computing processor. By drawing on the structure of biological neural networks, such as the transmission mode between neurons in the human brain, it can quickly process input information and can also continuously self-learn. Through NPU, applications such as intelligent cognition of electronic device 100 can be realized, such as image recognition, face recognition, voice recognition, text understanding, etc.

[0131] The external memory interface 120 can be used to connect an external memory card, such as a Micro SD card, to expand the storage capacity of the electronic device 100. The external memory card communicates with the processor 110 through the external memory interface 120 to implement a data storage function, such as storing music, video and other files in the external memory card.

[0132] The internal memory 121 can be used to store computer executable program codes, which include instructions. The internal memory 121 may include a program storage area and a data storage area. Among them, the program storage area may store an operating system, an application required for at least one function (such as a sound playback function, an image playback function, etc.), etc. The data storage area may store data created during the use of the electronic device 100 (such as audio data, a phone book, etc.), etc. In addition, the internal memory 121 may include a high-speed random access memory, and may also include a non-volatile memory, such as at least one disk storage device, a flash memory device, a universal flash storage (UFS), etc. The processor 110 executes various functional applications and data processing of the electronic device 100 by running instructions stored in the internal memory 121, and / or instructions stored in a memory provided in the processor.

[0133] The electronic device 100 can implement audio functions such as music playing, recording, voice calls, video calls, etc. through the audio module 170, the speaker 170A, the receiver 170B, the microphone 170C, the headphone jack 170D, and the application processor.

[0134] The pressure sensor 180A is used to sense the pressure signal and can convert the pressure signal into an electrical signal. In some embodiments, the pressure sensor 180A can be set on the display screen 194. There are many types of pressure sensors 180A, such as resistive pressure sensors, inductive pressure sensors, capacitive pressure sensors, etc. The capacitive pressure sensor can be a parallel plate including at least two conductive materials. When a force acts on the pressure sensor 180A, the capacitance between the electrodes changes. The electronic device 100 determines the intensity of the pressure according to the change in capacitance. When a touch operation acts on the display screen 194, the electronic device 100 detects the touch operation intensity according to the pressure sensor 180A. The electronic device 100 can also calculate the touch position according to the detection signal of the pressure sensor 180A. In some embodiments, touch operations acting on the same touch position but with different touch operation intensities can correspond to different operation instructions. For example: when a touch operation with a touch operation intensity less than the first pressure threshold acts on the short message application icon, an instruction to view the short message is executed. When a touch operation with a touch operation intensity greater than or equal to the first pressure threshold acts on the short message application icon, an instruction to create a new short message is executed.

[0135] The gyro sensor 180B can be used to determine the motion posture of the electronic device 100. In some embodiments, the angular velocity of the electronic device 100 around three axes (i.e., x, y, and z axes) can be determined by the gyro sensor 180B. The gyro sensor 180B can be used for anti-shake shooting. For example, when the shutter is pressed, the gyro sensor 180B detects the angle of the electronic device 100 shaking, calculates the distance that the lens module needs to compensate based on the angle, and allows the lens to offset the shaking of the electronic device 100 through reverse movement to achieve anti-shake. The gyro sensor 180B can also be used for navigation and somatosensory game scenes.

[0136] The air pressure sensor 180C is used to measure air pressure. In some embodiments, the electronic device 100 calculates the altitude through the air pressure value measured by the air pressure sensor 180C to assist positioning and navigation.

[0137] The magnetic sensor 180D includes a Hall sensor. The electronic device 100 can use the magnetic sensor 180D to detect the opening and closing of the flip leather case. In some embodiments, when the electronic device 100 is a flip phone, the electronic device 100 can detect the opening and closing of the flip cover according to the magnetic sensor 180D. Then, according to the detected opening and closing state of the leather case or the opening and closing state of the flip cover, the flip cover can be automatically unlocked.

[0138] The acceleration sensor 180E can detect the magnitude of the acceleration of the electronic device 100 in all directions (generally three axes). When the electronic device 100 is stationary, the magnitude and direction of gravity can be detected. It can also be used to identify the posture of the electronic device and is applied to applications such as horizontal and vertical screen switching and pedometers.

[0139] The distance sensor 180F is used to measure the distance. The electronic device 100 can measure the distance by infrared or laser. In some embodiments, when shooting a scene, the electronic device 100 can use the distance sensor 180F to measure the distance to achieve fast focusing.

[0140] The proximity light sensor 180G may include, for example, a light emitting diode (LED) and a light detector, such as a photodiode. The light emitting diode may be an infrared light emitting diode. The electronic device 100 emits infrared light outward through the light emitting diode. The electronic device 100 uses a photodiode to detect infrared reflected light from nearby objects. When sufficient reflected light is detected, it can be determined that there is an object near the electronic device 100. When insufficient reflected light is detected, the electronic device 100 can determine that there is no object near the electronic device 100. The electronic device 100 can use the proximity light sensor 180G to detect that the user holds the electronic device 100 close to the ear to talk, so as to automatically turn off the screen to save power. The proximity light sensor 180G can also be used in leather case mode and pocket mode to automatically unlock and lock the screen.

[0141] The ambient light sensor 180L is used to sense the ambient light brightness. The electronic device 100 can adaptively adjust the brightness of the display screen 194 according to the perceived ambient light brightness. The ambient light sensor 180L can also be used to automatically adjust the white balance when taking pictures. The ambient light sensor 180L can also cooperate with the proximity light sensor 180G to detect whether the electronic device 100 is in a pocket to prevent accidental touches.

[0142] The fingerprint sensor 180H is used to collect fingerprints. The electronic device 100 can use the collected fingerprint characteristics to implement fingerprint unlocking, access application locks, fingerprint photography, fingerprint call answering, etc.

[0143] The temperature sensor 180J is used to detect temperature. In some embodiments, the electronic device 100 uses the temperature detected by the temperature sensor 180J to execute a temperature processing strategy. For example, when the temperature reported by the temperature sensor 180J exceeds a threshold, the electronic device 100 reduces the performance of a processor located near the temperature sensor 180J to reduce power consumption and implement thermal protection. In other embodiments, when the temperature is lower than another threshold, the electronic device 100 heats the battery 142 to avoid abnormal shutdown of the electronic device 100 due to low temperature. In other embodiments, when the temperature is lower than another threshold, the electronic device 100 performs a boost on the output voltage of the battery 142 to avoid abnormal shutdown caused by low temperature.

[0144] The touch sensor 180K is also called a "touch control device". The touch sensor 180K can be set on the display screen 194. The touch sensor 180K and the display screen 194 form a touch screen, also called a "touch control screen". The touch sensor 180K is used to detect touch operations acting on or near it. The touch sensor can pass the detected touch operation to the application processor to determine the type of touch event. Visual output related to the touch operation can be provided through the display screen 194. In other embodiments, the touch sensor 180K can also be set on the surface of the electronic device 100, which is different from the position of the display screen 194.

[0145] The bone conduction sensor 180M can obtain a vibration signal. In some embodiments, the bone conduction sensor 180M can obtain a vibration signal of a vibrating bone block of the vocal part of the human body. The bone conduction sensor 180M can also contact the human pulse to receive a blood pressure beat signal. In some embodiments, the bone conduction sensor 180M can also be set in an earphone and combined into a bone conduction earphone. The audio module 170 can parse out a voice signal based on the vibration signal of the vibrating bone block of the vocal part obtained by the bone conduction sensor 180M to realize a voice function. The application processor can parse the heart rate information based on the blood pressure beat signal obtained by the bone conduction sensor 180M to realize a heart rate detection function.

[0146] The key 190 includes a power key, a volume key, etc. The key 190 may be a mechanical key or a touch key. The electronic device 100 may receive key input and generate key signal input related to user settings and function control of the electronic device 100.

[0147] Motor 191 can generate vibration prompts. Motor 191 can be used for incoming call vibration prompts, and can also be used for touch vibration feedback. For example, touch operations acting on different applications (such as taking pictures, audio playback, etc.) can correspond to different vibration feedback effects. For touch operations acting on different areas of the display screen 194, motor 191 can also correspond to different vibration feedback effects. Different application scenarios (for example: time reminders, receiving messages, alarm clocks, games, etc.) can also correspond to different vibration feedback effects. The touch vibration feedback effect can also support customization.

[0148] Indicator 192 may be an indicator light, which may be used to indicate charging status, power changes, messages, missed calls, notifications, etc.

[0149] The electronic device provided in this embodiment is used to execute the above method, so the same effect as the above implementation method can be achieved. In the case of an integrated unit, the electronic device may include a processing module, a storage module and a communication module. Among them, the processing module can be used to control and manage the actions of the electronic device, for example, it can be used to support the electronic device to execute the steps performed by the processing unit. The storage module can be used to support the electronic device to execute stored program codes and data, etc. The communication module can be used to support the communication between the electronic device and other devices.

[0150] The software system of the electronic device 100 may adopt a layered architecture, an event-driven architecture, a micro-kernel architecture, a micro-service architecture, or a cloud architecture. The embodiment of the present invention takes the Android system of the layered architecture as an example to illustrate the software structure of the electronic device 100. It should be noted that in the embodiment of the present application, the operator system of the electronic device may include but is not limited to (Symbian), (Android), (iOS), (Blackberry), Hongmeng (HarmonyOS) and other operating systems, this application does not make any limitation. Fig.13 A software structure block diagram of the electronic device 100 provided in an embodiment of the present application is shown.

[0151] The layered architecture divides the software into several layers, each with clear roles and division of labor. The layers communicate with each other through software interfaces. In some embodiments, the Android system is divided into four layers, from top to bottom: the application layer, the application framework layer, the Android runtime and system library, and the kernel layer.

[0152] like Fig.13 As shown, the application layer may include applications such as camera, gallery, calendar, call, map, navigation, WLAN, Bluetooth, music, video, short message, etc.

[0153] The application framework layer provides an application programming interface (API) and a programming framework for the applications in the application layer. The application framework layer includes some predefined functions.

[0154] like Fig.13 As shown, the application framework layer may include a window manager, a content provider, a view system, a phone manager, a resource manager, a notification manager, and the like.

[0155] The window manager is used to manage window programs. The window manager can obtain the display screen size, determine whether there is a status bar, lock the screen, capture the screen, etc.

[0156] Content providers are used to store and retrieve data and make it accessible to applications. The data may include videos, images, audio, calls made and received, browsing history and bookmarks, phone books, etc.

[0157] The view system includes visual controls, such as controls for displaying text, controls for displaying images, etc. The view system can be used to build applications. A display interface can be composed of one or more views. For example, a display interface including a text notification icon can include a view for displaying text and a view for displaying images.

[0158] The phone manager is used to provide communication functions of the electronic device 100, such as management of call status (including connecting, hanging up, etc.).

[0159] The resource manager provides various resources for applications, such as localized strings, icons, images, layout files, video files, and so on.

[0160] The notification manager enables applications to display notification information in the status bar. It can be used to convey notification-type messages and can disappear automatically after a short stay without user interaction. For example, the notification manager is used to notify download completion, message reminders, etc. The notification manager can also be a notification that appears in the system top status bar in the form of a chart or scroll bar text, such as notifications of applications running in the background, or a notification that appears on the screen in the form of a dialog window. For example, a text message is displayed in the status bar, a prompt sound is emitted, an electronic device vibrates, an indicator light flashes, etc.

[0161] Android Runtime includes core libraries and virtual machines. Android runtime is responsible for scheduling and management of the Android system.

[0162] The core library consists of two parts: one part is the function that needs to be called by the Java language, and the other part is the Android core library.

[0163] The application layer and the application framework layer run in a virtual machine. The virtual machine executes the Java files of the application layer and the application framework layer as binary files. The virtual machine is used to perform functions such as object life cycle management, stack management, thread management, security and exception management, and garbage collection.

[0164] The system library may include multiple functional modules, such as surface manager, media library, 3D graphics processing library (such as OpenGL ES), 2D graphics engine (such as SGL), etc.

[0165] The surface manager is used to manage the display subsystem and provide the fusion of 2D and 3D layers for multiple applications.

[0166] The media library supports playback and recording of a variety of commonly used audio and video formats, as well as static image files, etc. The media library can support a variety of audio and video encoding formats, such as: MPEG4, H.264, MP3, AAC, AMR, JPG, PNG, etc.

[0167] The 3D graphics processing library is used to implement 3D graphics drawing, image rendering, compositing, and layer processing.

[0168] A 2D graphics engine is a drawing engine for 2D drawings.

[0169] The kernel layer is the layer between hardware and software. The kernel layer contains at least display driver, camera driver, audio driver, and sensor driver.

[0170] like Fig.14 As shown, Fig.14 1400 is a schematic diagram of a structure of a device 1400 provided in an embodiment of the present application. The device may be an electronic device in an embodiment of the present application, or a chip or chip system in an electronic device. Fig.14 As shown, the device 1400 may include: a display unit 1401 and a processing unit 1402. The display unit 1401 is used to support the device 1300 to perform the above-mentioned display-related steps; the processing unit 1402 is used to support the device 1400 to perform the above-mentioned processing steps.

[0171] In a possible implementation, the device 1400 further includes a storage unit 1403. The storage unit 1403 and the processing unit 1402 are connected via a line. The storage unit 1403 may include one or more memories, and the memory may be a device used to store programs or data in one or more devices or circuits. The storage unit 1403 may exist independently and be connected to the processing unit 1402 via a communication bus. The storage unit 1403 may also be integrated with the processing unit 1402.

[0172] The storage unit 1403 can store computer-executable instructions of the method in the electronic device so that the processing unit 1402 executes the method in the above embodiment. The storage unit 1403 can be a register, a cache, or a random access memory (RAM), etc., or a read-only memory (ROM) or other types of static storage devices that can store static information and instructions.

[0173] Fig.15 This is a schematic diagram of the structure of a chip provided in an embodiment of the present application. Fig.15 As shown, the chip 1500 includes one or more (including two) processors 1501 , a communication line 1502 and a communication interface 1503 . Optionally, the chip 1500 also includes a memory 1504 .

[0174] In some implementations, the memory 1504 stores the following elements: executable modules or data structures, or a subset thereof, or an extended set thereof.

[0175] The method described in the above embodiment of the present application can be applied to the processor 1501, or implemented by the processor 1501. The processor 1501 may be an integrated circuit chip with signal processing capabilities. In the implementation process, each step of the above method can be completed by an integrated logic circuit of hardware or software instructions in the processor 1501. The above processor 1501 can be a general-purpose processor (for example, a microprocessor or a conventional processor), a digital signal processor, an application specific integrated circuit (ASIC), a field-programmable gate array (FPGA) or other programmable logic devices, discrete gates, transistor logic devices or discrete hardware components. The processor 1501 can implement or execute the disclosed methods, steps and logic block diagrams in the embodiments of the present application.

[0176] The steps of the method disclosed in the embodiment of the present application can be directly embodied as being executed by a hardware decoding processor, or being executed by a combination of hardware and software modules in the decoding processor. Among them, the software module can be located in a mature storage medium in the field such as a random access memory, a read-only memory, a programmable read-only memory, or an electrically erasable programmable read only memory (EEPROM). The storage medium is located in the memory 1504, and the processor 1501 reads the information in the memory 1504 and completes the steps of the above method in combination with its hardware.

[0177] The processor 1501 , the memory 1504 , and the communication interface 1503 may communicate with each other via the communication line 1502 .

[0178] In the above embodiments, the instructions stored in the memory for execution by the processor may be implemented in the form of a computer program product, wherein the computer program product may be pre-written in the memory, or may be downloaded and installed in the memory in the form of software.

[0179] The present application embodiment also provides a computer program product, which includes one or more computer instructions. When the computer program instructions are loaded and executed on the computer, the process or function according to the embodiment of the present application is generated in whole or in part. 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 computer-readable storage medium. For example, the computer instructions can be transmitted from a website site, a computer, a server or a data center by wired (e.g., coaxial cable, optical fiber, digital subscriber line (digital subscriber line, DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) mode to another website site, computer, server or data center. The computer-readable storage medium can be any available medium that a computer can store or a data storage device such as a server, a data center, etc. that includes one or more available media integrated. For example, the available medium can include a magnetic medium (e.g., a floppy disk, a hard disk or a tape), an optical medium (e.g., a digital versatile disc (digital versatile disc, DVD)), or a semiconductor medium (e.g., a solid state drive (solid state disk, SSD)), etc.

[0180] An embodiment of the present application provides an electronic device, which includes a processor and a memory, wherein the memory is used to store a computer program, and the processor is used to execute the computer program to perform the above method.

[0181] The embodiment of the present application provides a chip. The chip includes a processor, and the processor is used to call a computer program in a memory to execute the technical solution in the above embodiment. Its implementation principle and technical effect are similar to those of the above related embodiments, and will not be repeated here.

[0182] In the embodiments provided in the present application, it should be understood that the disclosed device / electronic device and method can be implemented in other ways. For example, the device / electronic device embodiments described above are only schematic, for example, the division of the modules or units is only a logical function division, and there may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point, the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms. In addition, each functional unit in each embodiment of the present application can be integrated in a processing unit, or each unit can exist physically separately, or two or more units can be integrated in one unit. The above-mentioned integrated unit can be implemented in the form of hardware or in the form of software functional units.

[0183] The embodiment of the present application also provides a computer-readable storage medium, which stores a computer program, and when the computer program is executed by a processor, the steps in the above-mentioned various method embodiments can be implemented. The computer-readable storage medium stores a computer program or instruction. The above-mentioned method is implemented when the computer program or instruction is executed by the processor. The method described in the above embodiment can be implemented in whole or in part by software, hardware, firmware, or any combination thereof. If implemented in software, the function can be stored as one or more instructions or codes on a computer-readable medium or transmitted on a computer-readable medium. Computer-readable media may include computer storage media and communication media, and may also include any medium that can transfer a computer program from one place to another. The storage medium may be any target medium accessible by a computer.

[0184] As a possible design, the computer-readable medium may include a compact disc read-only memory (CD-ROM), RAM, ROM, EEPROM or other optical disc storage; the computer-readable medium may include a magnetic disk storage or other magnetic disk storage device. Moreover, any connecting line may also be appropriately referred to as a computer-readable medium. For example, if the software is transmitted from a website, server or other remote source using a coaxial cable, fiber optic cable, twisted pair, DSL or wireless technology (such as infrared, radio and microwave), the coaxial cable, fiber optic cable, twisted pair, DSL or wireless technology such as infrared, radio and microwave are included in the definition of the medium. Disks and optical discs as used herein include compact discs (CDs), laser discs, optical discs, DVDs, floppy disks and Blu-ray discs, where disks generally reproduce data magnetically, while optical discs reproduce data optically using lasers. Combinations of the above should also be included in the scope of computer-readable media.

[0185] In the above description, specific details such as specific system structures, technologies, etc. are provided for the purpose of illustration rather than limitation, so as to provide a thorough understanding of the embodiments of the present application. However, it should be clear to those skilled in the art that the present application may also be implemented in other embodiments without these specific details. In other cases, detailed descriptions of well-known systems, devices, circuits, and methods are omitted to prevent unnecessary details from obstructing the description of the present application.

[0186] It should be understood that when used in the present specification and the appended claims, the term "comprising" indicates the presence of described features, wholes, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, wholes, steps, operations, elements, components and / or combinations thereof.

[0187] It should also be understood that the "multiple" mentioned in the specification and the appended claims of this application refers to two or more. In the description of this application, unless otherwise specified, " / " means or, for example, A / B can mean A or B; "and / or" in this article is only a description of the association relationship of associated objects, which means any combination of one or more of the items listed in the association and all possible combinations, and includes these combinations, for example, A and / or B can mean: A exists alone, A and B exist at the same time, and B exists alone.

[0188] In addition, in order to clearly describe the technical solution of the present application, words such as "first" and "second" are used to distinguish between identical or similar items with substantially the same functions and effects. Those skilled in the art can understand that words such as "first" and "second" do not limit the quantity and execution order, and cannot be understood as indicating or implying relative importance, and words such as "first" and "second" do not necessarily limit differences.

[0189] References to "one embodiment" or "some embodiments" etc. described in the specification of this application mean that one or more embodiments of the present application include specific features, structures or characteristics described in conjunction with the embodiment. Therefore, the phrases "in one embodiment", "in some embodiments", "in some other embodiments", "in some other embodiments", etc. appearing in different places in this specification do not necessarily refer to the same embodiment, but mean "one or more but not all embodiments", unless otherwise specifically emphasized in other ways.

[0190] The embodiments described above are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, a person skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. Such modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application, and should all be included in the protection scope of the present application.

Claims

1. A method for assessing blood pressure risk during pregnancy, characterized in that: Applied to electronic equipment, the method comprises: In the current pregnancy cycle, according to the first model and the first feature of the photoplethysmogram signal, a prediction result of the blood circulation state in the next pregnancy cycle is obtained, according to the second feature and the second model, a prediction result of the mental health state in the next pregnancy cycle is obtained, and according to the third feature and the third model, a prediction result of the blood pressure fluctuation state in the next pregnancy cycle is obtained, wherein the first feature, the second feature and the third feature are all data collected in the current pregnancy cycle; Determine coefficients corresponding to the prediction results of the blood circulation state, the mental health state, and the blood pressure fluctuation state, respectively, wherein the coefficients are used to measure the risk levels of different prediction results; Determining a risk assessment score for blood pressure in the next pregnancy cycle according to coefficients corresponding to the prediction results of the blood circulation state, the mental health state, and the blood pressure fluctuation state; When the risk assessment score is in the first interval, determining the risk level of blood pressure in the next pregnancy cycle as a no-risk level; When the risk assessment score is in the second interval, the risk level of the blood pressure in the next pregnancy cycle is determined to be a risky level.

2. The method according to claim 1, characterized in that The second interval includes a third interval, a fourth interval, and a fifth interval in sequence, and when the risk assessment score is in the second interval, determining the risk level of blood pressure in the next pregnancy cycle as a risky level includes: When the risk assessment score is in the third interval, determining the risk level of blood pressure in the next pregnancy cycle as the first risk level; When the risk assessment score is in the fourth interval, determining the risk level of blood pressure in the next pregnancy cycle as the second risk level; When the risk assessment score is in the fifth interval, determining the risk level of blood pressure in the next pregnancy cycle as the third risk level; According to the risk level of blood pressure in the next pregnancy cycle, prompt information corresponding to the first risk level, the second risk level, or the third risk level is output.

3. The method according to claim 2, characterized in that The outputting of prompt information corresponding to the first risk level, the second risk level, or the third risk level includes: A first interface is displayed, wherein the first interface includes the first risk level, the second risk level, or the third risk level, and corresponding prompt information.

4. The method according to any one of claims 1 to 3, characterized in that The first feature includes at least one of the following: the peak transmission time between different wavelengths in two adjacent cardiac cycles, the maximum rise speed transmission time between different wavelengths in two adjacent cardiac cycles, the amplitude ratio of the pulse wave peak to the starting point, the amplitude ratio of the pulse wave peak to the trough, and the time interval between the pulse wave peak and the dicrotic wave trough.

5. The method according to any one of claims 1 to 3, characterized in that The second feature includes at least one of the following: heart rate variability in the current pregnancy cycle, sleep duration in the current pregnancy cycle, light exposure duration in the current pregnancy cycle, and air pressure changes in the current pregnancy cycle.

6. The method according to any one of claims 1 to 3, characterized in that The third feature includes at least one of the following: user age, user's current pregnancy period, body mass index during the current pregnancy period and body mass index during the previous pregnancy period, blood pressure during the previous pregnancy period, and waveform characteristics of the photoplethysmogram.

7. An electronic device, characterized in that: include: one or more processors; one or more memories; The memory stores one or more programs, and when the one or more programs are executed by the processor, the electronic device executes the method according to any one of claims 1 to 6.

8. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores instructions, which, when executed on a computer, enable the computer to execute the method according to any one of claims 1 to 6.

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