Health monitoring information determination method and device, electronic equipment and storage medium

Abstract

The invention provides a health monitoring information determination method and device, electronic equipment and a computer readable storage medium, and relates to the technical field of vital sign recognition. The health monitoring information determination method comprises the following steps: acquiring biological characteristics according to wireless signal information of a scene where a target user is located, wherein the biological characteristics comprise a first biological characteristic corresponding to a sleep state and a second biological characteristic corresponding to a non-sleep state; determining a sleep quality evaluation result of the target user based on the first biological feature; acquiring a third biological feature after the target user executes the target action, wherein the third biological feature is used for reflecting the biological feature recovery capability after the target user executes the target action; and determining health monitoring information in combination with the second biological characteristics, the third biological characteristics and the sleep quality evaluation result. According to the invention, the health data of the user can be conveniently and timely processed, so that the user is reminded and rescued.

Description

Background Art

[0002] With the development of society and the advancement of science and technology, the fast-paced life has an impact on human health. For example, the number of people in sub-health is gradually increasing, and being in a sub-healthy state for a long time is very detrimental to human health. How to conduct early monitoring and early intervention for groups with potential health threats is particularly important.

[0003] In the related art, users are required to wear special equipment for health checks. The equipment is expensive and inconvenient to operate. Moreover, the device can only respond to abnormal situations when the user shows obvious abnormalities. However, the opportunity for treatment may have been missed, affecting the user's health. Summary of the invention

[0004] The purpose of the present disclosure is to provide a method for determining health monitoring information, a device for determining health monitoring information, an electronic device and a computer-readable storage medium, so as to facilitate and timely process the user's health data to at least a certain extent, so as to remind and rescue the user.

[0005] According to a first aspect of the present disclosure, a method for determining health monitoring information is provided, including: acquiring biometric characteristics based on wireless signal information of a scene in which a target user is located, the biometric characteristics including a first biometric characteristic corresponding to a sleeping state and a second biometric characteristic corresponding to a non-sleeping state; determining a sleep quality evaluation result of the target user based on the first biometric characteristic; acquiring a third biometric characteristic after the target user performs a target action, the third biometric characteristic being used to reflect the biometric recovery ability of the target user after the target action is performed; and determining health monitoring information in combination with the second biometric characteristic, the third biometric characteristic and the sleep quality evaluation result.

[0006] According to a second aspect of the present disclosure, a device for determining health monitoring information is provided, including: a first feature acquisition module, used to acquire biometric characteristics based on wireless signal information of a scene in which a target user is located, the biometric characteristics including a first biometric characteristic corresponding to a sleeping state and a second biometric characteristic corresponding to a non-sleeping state; a first processing module, used to determine a sleep quality evaluation result of the target user based on the first biometric characteristic; a second feature acquisition module, used to acquire a third biometric characteristic of the target user after the target user performs a target action, the third biometric characteristic being used to reflect the biometric recovery ability of the target user after the target user performs the target action; and a second processing module, used to determine the health monitoring information in combination with the second biometric characteristic, the third biometric characteristic and the sleep quality evaluation result.

[0007] According to a third aspect of the present disclosure, there is provided an electronic device, comprising: a processor; and a memory for storing one or more programs, which, when the one or more programs are executed by one or more processors, enables the one or more processors to implement the above method.

[0008] According to a fourth aspect of the present disclosure, a computer-readable storage medium is provided, on which a computer program is stored, and when the computer program is executed by a processor, the above method is implemented.

[0009] The method for determining health monitoring information provided by the embodiment of the present disclosure, on the one hand, obtains a first biometric feature corresponding to a sleeping state and a second biometric feature corresponding to a non-sleeping state through wireless signal information of a scene in which a target user is located received by a terminal device, determines a sleep quality evaluation result of the target user based on the first biometric feature, and realizes imperceptible monitoring of the sleep quality of the target user, so as to take sleep quality as one of the factors affecting health monitoring information; on the other hand, obtains a third biometric feature after the target user performs a target action, and realizes imperceptible monitoring of the target user's ability to recover life characteristics after performing the action, taking into account the difference in the ability to recover life characteristics of users with potential health problems and healthy users after performing the same action. On the other hand, the health monitoring information is determined by combining the second biometric, the third biometric and the sleep quality evaluation results. This process combines the static health data (sleep state) and dynamic health data (after executing the target action) of the target user. Without increasing the hardware cost, the target user does not need to wear any additional equipment. It is a completely contactless health monitoring process, which can process the health data of the target user in a timely manner, so as to achieve early monitoring and early intervention of the health status of the target user and reduce the cost of health monitoring.

[0010] It is to be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the present disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] The drawings herein are incorporated into the specification and constitute a part of the specification, showing embodiments consistent with the present disclosure, and together with the specification, are used to explain the principles of the present disclosure. Obviously, the drawings described below are only some embodiments of the present disclosure, and for ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work. In the drawings:

[0012] Figure 1 A health monitoring information determination system diagram involved in the health monitoring information determination method of an embodiment of the present disclosure is shown;

[0013] Figure 2 A flowchart schematically illustrates a method for determining health monitoring information according to an exemplary embodiment of the present disclosure;

[0014] Figure 3A flowchart schematically illustrates an implementation method of acquiring biometric features according to wireless signal information in an exemplary embodiment of the present disclosure;

[0015] Figure 4 A schematic diagram schematically illustrates a method of decomposing channel state information in an exemplary embodiment of the present disclosure;

[0016] Figure 5 A schematic diagram schematically shows the channel state information before and after filtering in an exemplary embodiment of the present disclosure;

[0017] Figure 6 A flowchart schematically illustrates another implementation method of determining a target user's sleep quality evaluation result in an exemplary embodiment of the present disclosure;

[0018] Figure 7 A flowchart schematically illustrates an implementation method of acquiring a third biometric feature according to an exemplary embodiment of the present disclosure;

[0019] Figure 8 A schematic diagram schematically illustrating another method of determining a third biometric feature in an exemplary embodiment of the present disclosure;

[0020] Fig. 9 A schematic diagram schematically illustrates an interactive interface diagram in an exemplary embodiment of the present disclosure;

[0021] Fig.10 A schematic diagram schematically illustrates a method of acquiring motion biological characteristics in an exemplary embodiment of the present disclosure;

[0022] Fig.11 A schematic diagram of an interface for providing health reminder information in an exemplary embodiment of the present disclosure is schematically shown;

[0023] Fig.12 Schematically showing another interface diagram for providing health reminder information in an exemplary embodiment of the present disclosure;

[0024] Fig.13 A flowchart schematically illustrating another method of providing health reminder information in an exemplary embodiment of the present disclosure;

[0025] Fig.14 A complete flow chart of a health monitoring method in an exemplary embodiment of the present disclosure is schematically shown;

[0026] Fig.15 Schematically showing an interface diagram for presenting prompt information in an exemplary embodiment of the present disclosure;

[0027] Fig.16 A structural diagram schematically shows a health monitoring information determination device in an exemplary embodiment of the present disclosure;

[0028] Fig.17 The following is a schematic diagram schematically showing an electronic device to which the embodiments of the present disclosure can be applied. DETAILED DESCRIPTION

[0029] Example embodiments will now be described more fully with reference to the accompanying drawings. However, example embodiments can be implemented in a variety of forms and should not be construed as limited to the examples set forth herein; rather, these embodiments are provided so that the disclosure will be more comprehensive and complete and to fully convey the concepts of the example embodiments to those skilled in the art. The described features, structures, or characteristics may be combined in any suitable manner in one or more embodiments.

[0030] In addition, the accompanying drawings are only schematic illustrations of the present disclosure and are not necessarily drawn to scale. The same reference numerals in the figures represent the same or similar parts, and their repeated description will be omitted. Some of the block diagrams shown in the accompanying drawings are functional entities and do not necessarily correspond to physically or logically independent entities. These functional entities can be implemented in software form, or implemented in one or more hardware modules or integrated circuits, or implemented in different networks and / or processor devices and / or microcontroller devices.

[0031] Figure 1 FIG. 1 shows a system diagram of health monitoring information determination involved in the health monitoring information determination method of the embodiment of the present disclosure. Figure 1 As shown, the system includes a signal transmitting device Tx (such as a WIFI wireless router) and a signal receiving device Rx, and the signal transmitting device Tx and the signal receiving device Rx each have two or more receiving antennas. The signal transmitting device Tx transmits wireless signals, and the signal receiving device Rx receives wireless information and collects wireless signal information.

[0032] When there is no monitored user in the wireless environment, the wireless signal received by the signal receiving device Rx and the corresponding wireless signal information are not interfered with; on the contrary, when there is a monitored target user in the wireless environment, the presence of the target user will cause changes in the wireless signal. For example, the target user's breathing causes slight changes in the wireless signal, and the purpose of monitoring the target user's health status can be achieved by collecting wireless signal information.

[0033] In the disclosed embodiment, the provided health monitoring information determination method can be executed by a terminal device. The terminal device, as a signal receiving device, obtains the first biometric feature corresponding to the sleep state and the second biometric feature corresponding to the awake state according to the wireless signal information of the scene where the target user is located, and determines the sleep evaluation result of the target user based on the first biometric feature; obtains the third biometric feature after the target user performs the target action, and then combines the second biometric feature, the third biometric feature and the sleep quality evaluation result to obtain health monitoring information. In the case where all steps in the health monitoring information determination method provided in the disclosed embodiment can be executed by the terminal device, all steps can be executed by the terminal device processor.

[0034] The terminal device can be an intelligent device with data processing capabilities, such as a smart phone, computer, tablet computer, vehicle-mounted device, wearable device, monitoring device and other intelligent devices. The terminal device can also be called a mobile terminal, terminal, mobile device, etc. The present disclosure does not limit the type of terminal device.

[0035] Furthermore, the health monitoring information determination method provided in the embodiment of the present disclosure can also be executed by a server. Correspondingly, in this mode of execution by the server, the server can start executing the steps in the technical solution of the embodiment of the present disclosure in response to a trigger command, wherein the trigger command can be sent by a terminal device used by the user, or can be triggered locally by the server in response to some automation events. The server can receive the wireless signal information sent by the terminal device, and then execute the steps of the embodiment of the present disclosure.

[0036] The server may be a background system that provides relevant services in the embodiments of the present disclosure, and may include one electronic device with computing functions, such as a portable computer, a desktop computer, a smart phone, or a cluster formed by multiple electronic devices.

[0037] In addition, the technical solution of the embodiment of the present disclosure can also be executed collaboratively by the terminal device and the server. In this way of collaborative execution by the electronic device and the server, in this way of the embodiment of the present disclosure, some steps in the technical solution provided by the embodiment of the present disclosure are executed by the terminal device, and other steps are executed by the server. For example, the technical solution provided by the embodiment of the present disclosure can be executed by the server to obtain biometric features based on the wireless signal information of the scene in which the target user is located, and send the biometric features to the server, and the server determines the sleep quality evaluation result of the target user based on the first biometric feature; and determines the health monitoring information in combination with the second biometric feature, the third biometric feature and the sleep quality evaluation result. The server can also send the health monitoring information to the terminal device associated with the target user.

[0038] It should be noted that in this method in which the terminal device and the server are executed collaboratively, the steps executed by the terminal device and the server respectively can be dynamically adjusted according to actual conditions, and there is no special restriction on this.

[0039] In the embodiments of the present disclosure, the technical solution is executed by a terminal device as an example for description.

[0040] At present, the number of people with potential health threats is gradually increasing. For example, people who have been in sub-health status for a long time usually check or take measures when the symptoms are obvious, which may have missed the best time for treatment, or even threaten their lives. In many cases, the body has actually given relevant problem signals long ago, but it has not attracted enough attention and vigilance.

[0041] In the related art, the human body's magnetic field frequency is detected through the principle of magnetic oscillation to calculate the body's fatigue level. When the fatigue value is between 60 and 80, it is a normal state, less than 60 is excessive fatigue, and 80 is long-term fatigue. However, this method lacks accuracy and stability.

[0042] Alternatively, users may seek medical attention only when an obvious abnormality occurs, or may need to use expensive additional equipment for examination, which usually responds to abnormal conditions when the user has obvious abnormalities. In these cases, users miss the opportunity for early intervention, which affects their physical health.

[0043] Based on one or more of the above problems, the purpose of the embodiments of the present disclosure is to provide a method for timely processing user health data, normalize health monitoring, and achieve the purpose of health reminders and assistance for users. The embodiments of the present disclosure obtain health monitoring information by timely processing the health data of the target user, and then use the health monitoring information to monitor the health of the target user.

[0044] In the embodiments of the present disclosure, the method for determining health monitoring information can be applied to relevant scenarios of daily user's physical health monitoring. For example, the method steps of the embodiments of the present disclosure are executed by the user's terminal device to realize daily health monitoring. For another example, for groups that need to pay special attention to their physical condition (such as elderly people living alone), the health monitoring results can be determined by the method for determining health monitoring information of the embodiments of the present disclosure and sent to the associated terminal device, so that their guardians (such as children) can be informed of the elderly's physical condition in a timely manner and intervene in potential health threats at an early stage.

[0045] Furthermore, the health monitoring method of the embodiment of the present disclosure can also be applied to the scenario of health monitoring of users in relevant health institutions or groups. For example, in a hospital or nursing home, by implementing the method steps of the embodiment of the present disclosure, daily health monitoring can be achieved to guide relevant personnel in work navigation, early warning, etc. Figure 2As shown, the health monitoring information determination method of the embodiment of the present disclosure may include the following steps S210 to S240:

[0046] In step S210, biometric features are acquired based on wireless signal information of a scene where the target user is located, where the biometric features include a first biometric feature corresponding to a sleeping state and a second biometric feature corresponding to a non-sleeping state.

[0047] In an exemplary embodiment of the present disclosure, the scene in which the target user is located refers to the wireless environment scene of the target user in the health monitoring information determination system, and the presence of the target user causes the wireless signal information received by the terminal device to change. The biometric feature can be relevant biological information that can reflect the physical state of the target user, such as the target user's breathing frequency, heart rate, sleep duration, breathing during sleep, etc. The biometric feature can also be relevant information that can reflect the physical state of the target user obtained through statistics, such as the time it takes for the target user's breathing frequency to return to normal frequency after performing a certain action, the time it takes for the heart rate to return to normal heart rate after performing a certain action, etc.

[0048] Among them, the first biometric characteristic corresponding to the sleeping state is the biometric characteristic of the target user in the sleeping state obtained based on the wireless signal of the scene where the target user is located, such as the sleeping duration, the breathing frequency during sleep, etc., and the first biometric characteristic is the static health data of the target user. The second biometric characteristic corresponding to the awake state refers to the biometric characteristic obtained based on the wireless signal of the scene where the target user is located when the target user is not in the sleeping state, such as the breathing frequency and heart rate when awake.

[0049] The wireless signal in the scene where the target user is located can be selected from any one of WIFI signals, FMCW (Frequency Modulated Continuous Wave) signals, UWB (Ultra Wide Band) signals, Bluetooth, ultrasound, etc. The following embodiments of the present disclosure are described by taking the wireless signal as a WIFI signal as an example.

[0050] The first biometric feature and the second biometric feature corresponding to the target user can be obtained by collecting the wireless signal information of the target user in the wireless signal scene. It is worth noting that the first biometric feature and the second biometric feature can be collected in real time without the user's perception, or can be collected at preset intervals, which can be set accordingly according to user needs.

[0051] In step S220 , a sleep quality evaluation result of the target user is determined based on the first biometric feature.

[0052] In an exemplary embodiment of the present disclosure, the physical condition of the target user can be reflected to a certain extent in the sleep quality. The sleep quality can be determined by the sleep duration; or the sleep quality can be determined by comparing the currently determined sleep quality with the historical sleep quality of the target user to determine the sleep quality according to the comparison result.

[0053] The target user's sleep quality evaluation result can be determined by the first biometric feature collected when the target user is in a sleeping state. For example, if the first biometric feature includes sleep duration, deep sleep duration, breathing frequency and heart rate during sleep, etc., the sleep quality evaluation result can be determined in combination with these first biometric features.

[0054] In step S230, a third biometric feature is obtained after the target user performs the target action, where the third biometric feature is used to reflect the biometric feature recovery capability of the target user after the target action is performed.

[0055] In the exemplary embodiments of the present disclosure, the target action may be a pre-set designated action, a custom action of the target user according to his / her own needs, or a random action performed by the target user in his / her daily life. For example, skipping, sit-ups, jumping on the spot, climbing stairs, running, etc., without any special limitation. The biometric recovery capability refers to the time required for the target user's biometrics to return to normal (the standard of a healthy human body) after performing the target action.

[0056] In some possible embodiments, only one motion biometric characteristic (such as heart rate) may be selected as a dimensional feature for determining the third biometric characteristic; in other possible embodiments, at least two motion biometric characteristics (such as heart rate, breathing rate) may be selected as dimensional features for determining the third biometric characteristic, thereby increasing the accuracy and reliability of the third biometric characteristic by increasing the dimensionality of the motion biometric characteristic.

[0057] In some possible embodiments, the duration of the target action performed by the target user can be limited, that is, the third biometric feature is obtained after performing the target action for a preset duration, so as to avoid affecting the accuracy of the detection result due to different exercise durations of different users.

[0058] Because under normal conditions (such as not exercising), the performance difference between people with potential health problems and healthy people is not much, but after performing some actions, there are differences in the physical reactions and recovery abilities of the two groups. For example, after doing ten push-ups at the same time, the heart rate of a healthy user may quickly return to normal levels, but users with chronic diseases or potential health threats such as sub-health may need a longer recovery time. The disclosed embodiment uses the third biometric feature after the target user performs the target action, so that the biometric recovery ability of the target user after performing the target action is used as one of the factors to determine the health monitoring information, which makes it easier to discover the potential health problems of the target user, thereby improving the accuracy of the health monitoring information.

[0059] In step S240, health monitoring information is determined by combining the second biological characteristic, the third biological characteristic and the sleep quality evaluation result.

[0060] In an exemplary embodiment of the present disclosure, the health monitoring information is an indicator for judging whether the target user has potential health problems. For example, when the health monitoring information of the target user is higher than a preset standard, it is determined that the target user has potential health problems. For another example, when the health monitoring information is at a preset health level, it is determined that the target user has potential health problems.

[0061] Among them, the second biometric feature and the sleep quality evaluation result are used as the static health data of the target user, and the third biometric feature is used as the dynamic health data of the target user. The health monitoring information of the target user is comprehensively determined by combining the second biometric feature, the third biometric feature and the sleep quality evaluation result.

[0062] Through the method for determining health monitoring information of the embodiment of the present disclosure, on the one hand, the sleep quality evaluation result of the target user is determined based on the first biometric feature, so as to realize the imperceptible monitoring of the sleep quality of the target user, so as to take the sleep quality as one of the factors affecting the health monitoring information; on the other hand, the third biometric feature is obtained after the target user performs the target action, so as to realize the imperceptible monitoring of the target user's life feature recovery ability after performing the action. Considering that the life feature recovery level of users with potential health problems and healthy users after performing the same action is different, the life feature recovery ability (third biometric feature) is taken as one of the factors affecting the health monitoring information, so as to increase the determination dimension of the health monitoring information and improve the accuracy of the health monitoring information; on the other hand, the health monitoring information is determined by combining the second biometric feature, the third biometric feature and the sleep quality evaluation result. The process combines the static health data (sleep state) and dynamic health data (after performing the target action) of the target user. Without increasing the hardware cost, the target user does not need to wear any additional equipment. It is a completely contactless health monitoring process, and the health data of the target user can be processed in time to realize early monitoring and early intervention of the health status of the target user, and reduce the cost of health monitoring.

[0063] In an exemplary embodiment, a method for obtaining biometric features based on wireless signal information is provided. Figure 3 As shown, the wireless signal information may include a WIFI signal, and obtaining the biometric feature according to the wireless signal information of the scene where the target user is located may include steps S310 and S320:

[0064] Step S310: Acquire channel state information corresponding to the target user in the WIFI environment according to the WIFI signal.

[0065] See also Figure 1 As shown in the system diagram, after the terminal device is connected to the wireless WIFI router, the wireless WIFI router will feedback channel state information (CSI) to the terminal device, thereby enabling the terminal device to collect the channel state information corresponding to the target user.

[0066] CSI can describe the attenuation and phase shift experienced by WiFi signals during propagation. The biological characteristics of the human body will cause the measured value of CSI to change. For example, the rise and fall of the chest caused by human breathing causes the measured value of CSI to show quasi-periodic changes.

[0067] Step S320: Determine biometric features based on the channel state information.

[0068] In order to accurately obtain the biometric characteristics of the target user from the channel state information, the channel state information may be processed by filtering.

[0069] In an exemplary embodiment, if Figure 4 A schematic diagram of decomposing channel state information according to an exemplary embodiment of the present disclosure is shown. The process may include steps S410 to S430:

[0070] In step S410, the biometric type is determined.

[0071] Different biometric features require corresponding filtering methods. For example, a person's breathing rate is between 10 bmp and 40 bmp, that is, the breathing frequency is between 0.1667 Hz and 0.677 Hz, and the heart rate is between 60 times / minute and 100 times / minute, about 1.25 Hz to 1.42 Hz. To extract the corresponding biometric features from CSI, determine the biometric feature type and its corresponding frequency range.

[0072] Step S420: Filter the channel state information to obtain frequency band information corresponding to the frequency range of the biometric feature type.

[0073] The filtering method to be used is determined according to the frequency range of the biometric type. For example, if a matching filter is selected for filtering, the frequency band information corresponding to the frequency range of the biometric type can be obtained. In other words, only the signal of the frequency band corresponding to the frequency range of the biometric type is retained, and the background noise is excluded.

[0074] Figure 5 The schematic diagram of the channel state information before and after filtering is shown according to an exemplary embodiment of the present disclosure. By filtering the channel state information, the frequency band information of the human body mutual trust frequency and the frequency information of the human body heartbeat are obtained respectively.

[0075] Furthermore, for the detection of the target user's sleep duration and deep sleep duration, the brain wave signals of the human body in the sleep state or deep sleep state can also be obtained, and the channel state information can be filtered based on the frequency range corresponding to the brain wave signals to obtain the frequency band information in the sleep state or deep sleep state.

[0076] Step S430: Determine the biometric feature based on the frequency band information.

[0077] After the frequency band information is obtained, the biometric characteristics of the target user may be determined based on the frequency band information.

[0078] Taking the determination of breathing rate as an example, first, FFT (Fast Fourier Transform) can be used to convert the breathing signal into frequency, and the bilateral amplitude spectrum can be calculated, and the unilateral amplitude spectrum can be obtained based on the bilateral amplitude spectrum, so as to determine the frequency corresponding to the peak of the unilateral amplitude spectrum as the breathing frequency of the target user.

[0079] Taking the sleep duration as an example, the EEG signals generated during sleep are processed to divide the EEG signals into different sleep stages, and the duration of each sleep stage is counted.

[0080] It should be noted that the embodiments of the present disclosure may also use other methods to calculate various biometric features based on frequency band information, and there is no special limitation on this.

[0081] The disclosed embodiment obtains biometric features based on the wireless signal information of the scene where the target user is located, and can utilize the existing sensors and WIFI chips on the terminal device of the target user (such as mobile phones, computers, wearable devices, etc.), combined with a wireless WIFI router, without the need to introduce additional equipment and without increasing hardware costs. In addition, it avoids the target user from wearing additional equipment, realizes a contactless monitoring method, thereby reducing the target user's tension and avoiding the problem of inaccurate monitoring results caused by the user's emotions.

[0082] In an exemplary embodiment, a method for determining a sleep quality evaluation result of a target user is provided. Determining the sleep quality evaluation result of the target user based on the first biometric feature may include:

[0083] The first biological characteristic is input into the sleep quality evaluation model to obtain a sleep quality evaluation result; wherein the first biological characteristic at least includes sleep duration, deep sleep duration and breathing frequency in the sleep state.

[0084] The first biometric feature of the embodiment of the present disclosure may also include the posture type in the sleeping state, the number of posture changes, etc., which can be adaptively adjusted according to actual needs and is not particularly limited.

[0085] In some possible embodiments, before determining the sleep quality evaluation result of the target user based on the first biometric feature, a model may be trained using training sample data to obtain a sleep quality evaluation model.

[0086] Among them, sleep-related data is used as training sample data, such as user samples and their corresponding sleep duration, deep sleep duration, breathing frequency during sleep, etc. These training sample data are input into the model to be trained for training. The model to be trained can be any model that meets the requirements, such as a classification model, etc., and there is no special limitation on this.

[0087] In some possible embodiments, sleep quality evaluation models corresponding to different age levels can also be trained based on sample data of different age levels. For example, the user age can be divided into 0-15 years old, 15-25 years old, 25-30 years old, 30-40 years old, 40-50 years old and over 50 years old, and the sleep quality evaluation model can be trained using the training sample data of each age level.

[0088] Based on this, a corresponding sleep quality evaluation model may be determined from candidate sleep evaluation models according to the age group to which the target user belongs, and the first biological feature may be input to obtain a corresponding sleep quality evaluation result.

[0089] As users of different age groups grow older, their sleep duration begins to decrease. This is in line with biological laws and is not caused by potential physical health factors. By inputting the first biometric feature into a sleep quality model that matches the age level of the target user, the obtained sleep quality evaluation result is only related to the physical condition of the target user, excluding the influence of natural age.

[0090] In an exemplary embodiment, another implementation method for determining the sleep quality evaluation result of the target user is also provided. Figure 6 As shown, inputting the first biometric feature into the sleep quality evaluation model to obtain the sleep quality evaluation result may include step S610 and step S620:

[0091] Step S610: input the first biometric feature into the sleep quality evaluation model to obtain the model output result; Step S620: obtain the historical sleep quality evaluation results of the target user, and determine the sleep quality evaluation result according to the historical sleep quality evaluation results and the model output result.

[0092] The historical sleep quality evaluation result can be the average of the sleep quality evaluation results of the target user within a preset time period, or the highest value of the sleep quality evaluation results of the target user within the preset time period, or the previous sleep quality evaluation result of the target user in this test. It can be selected according to actual conditions and there is no special limitation on this.

[0093] In order to make the sleep quality evaluation results truly reflect the changes in the physical state of the target user, the sleep quality evaluation results are obtained by combining the current model output results with the target user's historical sleep quality evaluation results. The final sleep quality evaluation results are determined by horizontal comparison with the target user's own sleep quality to improve the accuracy and reliability of the sleep quality evaluation.

[0094] In some possible embodiments, the difference between the historical sleep quality evaluation result and the model output result can be taken as the sleep quality evaluation result, and the sleep quality evaluation result can be used to reflect the sleep quality changes of the target user as one of the monitoring factors of the health status.

[0095] In an exemplary embodiment, a method for obtaining a third biometric feature is provided. Figure 7 As shown, obtaining the third biometric feature of the target user after performing the target action may include steps S710 to S730:

[0096] Step S710: Based on the wireless signal information, obtain the motion biometric characteristics of the target user after performing the target action.

[0097] The sports biometrics are the biometrics of the target user after he / she has performed the target action, for example, the heart rate and breathing rate of the target user after he / she has done ten sit-ups.

[0098] The detailed process of acquiring motion biological characteristics based on wireless signals can be found in steps S410 to S430, which will not be described in detail here.

[0099] Step S720: Obtain the time required for the motion biometric feature to recover to a preset state.

[0100] The preset state may be a normal standard state corresponding to the motion biometrics, such as the heart rate and breathing rate in the non-motion state. The relevant biometrics of the target user in the non-motion state may be collected in advance as the preset state, or the state of the biometrics that meets medical standards may be used as the preset state, such as a heart rate of 60 to 100 beats per minute. The disclosed embodiments do not specifically limit this.

[0101] Step S730: Determine a third biometric feature based on the duration.

[0102] Users in different physical conditions may experience different lengths of time for their motion biometric characteristics to recover to a preset state after performing a specific action. For example, a person with potential health threats may need a longer time.

[0103] In some possible embodiments, the time required for the motion biometric characteristic to recover to a preset state can be directly used as the third biometric characteristic to characterize the biometric characteristic recovery ability of the target user after exercise.

[0104] In some possible embodiments, in order to further improve the accuracy of the third biometric feature, another method for determining the third biometric feature is provided.

[0105] like Figure 8 As shown, first, after the target user performs the target action, a duration is obtained through statistics; secondly, the corresponding correction weight is determined according to the action type of the target action, and the correction weight is pre-determined according to the biometric recovery ability of healthy users after performing actions of different types; finally, the third biometric feature is determined in combination with the correction weight and the above-mentioned duration.

[0106] For the same user, the time required for rope skipping and sit-ups may be different, and the difference may even be large. The purpose of setting the correction weight is to eliminate the influence of the action type on the third biometric feature, so that the third biometric feature is only related to the health status of the target user, excluding the influence of the action type.

[0107] The following describes a process of determining the correction weight corresponding to each action type based on the biometric recovery ability of a healthy user after performing actions of different action types.

[0108] First, for each action type, the biological ability recovery time of healthy users after performing the action type is counted; secondly, the biological ability recovery time of healthy users corresponding to different action types is compared, and a corresponding correction weight is assigned to each action type based on the comparison result. The correction weight makes the biological ability recovery time corresponding to each action type the same.

[0109] For example, for action type 1, action type 2, ..., action type N, the corresponding biological ability recovery time of a healthy user is a second, b seconds, ..., n seconds, respectively. After assigning correction weights x1, x2, ..., xn respectively, a×x1=b×x2……,=n×xn.

[0110] Furthermore, in actual implementation, the third biometric feature is determined in combination with the correction weight corresponding to the target action and the time required for it to recover to a preset state. This can eliminate the influence of the action type on the time, making the third biometric feature truly and completely dependent on the physical state of the target user, thereby improving the accuracy of determining the third biometric feature.

[0111] It should be noted that the above allocation weights a×x1=b×x2…,=n×xn are only exemplary. The disclosed embodiment may also determine the allocation weights in other ways so that the biological ability recovery time corresponding to each action type is the same, and there is no special limitation on this.

[0112] In an exemplary embodiment, if the target user has multiple motion biometric features after performing the target action, the duration corresponding to each motion biometric feature is obtained; further, the third biometric feature can be determined in combination with the duration corresponding to each motion biometric feature.

[0113] Among them, the average of the corresponding time lengths of each motion biological feature can be obtained as the third biometric feature, or the weighted average of the corresponding time lengths of each motion biological feature can be obtained according to preset weights, or the sum of the corresponding time lengths of each motion biological feature can be used as the third biometric feature, and so on. The embodiments of the present disclosure can be selected according to actual conditions and there is no special limitation on this.

[0114] For example, if the motion biometrics include breathing rate 2 and heart rate 2, and the time durations for the breathing rate 1 and heart rate 1 to recover to the preset state are t1 and t2 respectively, then (t1+t2) / 2 can be used as the third biometric.

[0115] The disclosed embodiment determines the third biometric feature by combining the time required for multiple motion biometric features of the target user to recover to the corresponding preset state after the target user performs the target action, thereby increasing the feature dimension for determining the third biometric feature, more comprehensively reflecting the recovery of the target user's physical state after performing the target action, and improving the accuracy of the third biometric feature.

[0116] In an exemplary embodiment, a method for determining the action type of a target action is provided. Before determining the third biometric feature based on the duration, it is also possible to:

[0117] In response to the test triggering operation, presenting candidate actions;

[0118] In response to the action selection operation, the action corresponding to the action selection operation is determined as a target action, and the action type of the target action is determined.

[0119] See also Fig. 9 An interactive interface diagram according to an exemplary embodiment of the present disclosure is shown, and the target user can Fig. 9 The interactive interface diagram shown triggers the test of the third biometric feature, and then the test of the third biometric feature is performed while the target user is conscious.

[0120] Among them, continue to see Fig. 9 As shown, after the target user triggers the test trigger operation, candidate actions can be presented for the target user to select. The candidate actions are pre-set actions, such as sit-ups, rope skipping, running, etc. The target user can select the target action according to his or her physical condition or personalized needs, that is, perform the action selection operation, and the action corresponding to the action selection operation is determined as the target action, and accordingly, the action type corresponding to the target action is obtained.

[0121] In addition, candidate actions of different action types may correspond to the same execution time. For example, if the execution time corresponding to each candidate action is set to 1 minute, after the target user selects the target action, the target user starts to continuously execute the target action for 1 minute. Accordingly, the biometric feature collected after 1 minute is the motion biometric feature.

[0122] For example, Fig.10 A schematic diagram of obtaining a motion biometric feature according to an exemplary embodiment of the present disclosure is shown. After the target user selects running as the target action, the target action starts to execute the running action, and the target user starts running. After the execution time of 1 minute, the breathing frequency and heart rate of the target user are collected, and then the time required for the motion biometric feature to recover to the preset state is started, which are m seconds and n seconds respectively, and finally the third biometric feature is determined by combining m seconds and n seconds.

[0123] By setting the execution time of the target action, the purpose is to unify the time for different users to execute different actions to be consistent, so as to avoid the influence of different execution times on the accuracy of the third biometric feature.

[0124] In another exemplary embodiment, another method for determining the action type of the target action is provided. Before determining the third biometric feature based on the duration, the action type of the target action can also be determined based on the wireless signal information.

[0125] In this exemplary embodiment, the third biometric feature can be acquired without the target user's awareness. Specifically, if it is determined based on the wireless signal that the target user is performing an action, the timing can be started and the motion biometric feature can be acquired after the execution time ends.

[0126] Among them, the wireless signal sent by the wireless WIFI router obtains its reflection in the surrounding environment. When the wireless signal passes through the target user, it will be reflected based on the body direction. Based on this, according to the signal value from each point in the space (i.e., RF snapshot), the RF snapshot can be used to identify motion events, that is, the action type of the target action can be identified. Of course, other methods can also be used to determine the action type of the target action performed by the target user based on the wireless signal information. The embodiment of the present disclosure does not limit the specific determination method.

[0127] Through the disclosed embodiments, the target user does not need to actively trigger the test, and the third biometric feature is collected without the target user's awareness. Usually, due to various reasons, the target user tends to ignore health problems and will not take the initiative to check or test when there is no obvious discomfort. The disclosed embodiments autonomously identify the target user's execution of the target action, and based on this, obtain the motion biometric feature and its action type, so as to obtain the third biometric feature without the user's awareness.

[0128] Furthermore, since the second biometric characteristic and the sleep quality evaluation result can also be obtained without the target user's perception, the entire process of determining the health monitoring information by combining the third biometric characteristic, the second biometric characteristic and the sleep quality evaluation result can be completely executed without the target user's active triggering or perception. By timely processing the target user's health data, the target user's health status can be monitored in near real time, which is conducive to early monitoring and intervention of health problems.

[0129] In an exemplary embodiment, another method for determining a third biometric characteristic is also provided. Determining the third biometric characteristic based on duration may include:

[0130] A distance value between the duration and a standard duration is obtained, where the standard duration is predetermined based on a biometric recovery duration of a healthy user after performing a target action; and a third biometric feature is determined based on the distance value.

[0131] The disclosed embodiment uses the distance value between the duration corresponding to the target user and the standard time difference as the third biometric feature, so that the third biometric feature reflects the difference in biometric recovery ability between the target user and a healthy human body. In other words, the duration corresponding to different users is obtained based on the biometric recovery ability of a healthy human body, which can further improve the accuracy of the third biometric feature.

[0132] In an exemplary embodiment, a method for determining health monitoring information is provided. The health monitoring information may be determined by combining the second biometric feature, the third biometric feature and the sleep quality evaluation result:

[0133] The second biometric feature, the third biometric feature and the sleep quality evaluation result are imported into the health status evaluation model to obtain health monitoring information; wherein the second biometric feature at least includes the breathing rate and heart rate of the target user when he is not sleeping.

[0134] In some possible embodiments, before determining the health monitoring information by combining the second biometric feature, the third biometric feature and the sleep quality evaluation result, a model may be trained using training sample data to obtain a health status evaluation model.

[0135] The sleep quality evaluation result samples, breathing frequency, heart rate and third biological characteristics of the collected sample users are used as training sample data, and these training sample data are input into the model to be trained for training. The model to be trained can be any model that meets the requirements, such as a classification model, etc., and there is no special limitation on this.

[0136] It should be noted that the second biometric feature may also include other related biometric features when not in sleep state, such as blood pressure, blood sample saturation, etc. The embodiments of the present disclosure include but are not limited to the above-mentioned second biometric features.

[0137] In an exemplary embodiment, after obtaining the health monitoring information of the target user, health monitoring is performed on the target user using the health monitoring information as a monitoring indicator.

[0138] In response to the health monitoring information satisfying the preset warning condition, health reminder information may be provided to the terminal of the associated user of the target user.

[0139] The preset warning condition may be that the value of the health monitoring information is greater than a preset threshold, or the preset warning condition may be that the data of the health monitoring information is greater than the preset threshold for more than a preset number of times, or that the value of the health monitoring information is at a preset warning level (multiple warning levels may be pre-set, such as a high level, a medium level, and a low level), etc. The embodiments of the present disclosure include but are not limited to the above-mentioned preset warning conditions.

[0140] The terminal associated with the target user may be a terminal held by the target user, or may be a terminal device associated with the terminal held by the target user, for example, a terminal of the target user's guardian, such as a relative, friend or caregiver.

[0141] See also Fig.11 A schematic diagram of an interface for providing health reminder information according to an exemplary embodiment of the present disclosure is shown. When the health monitoring information of the target user meets the preset warning condition, the health reminder information "You may be in sub-health, please relax" can be provided to the terminal associated with the target user.

[0142] In addition, related items related to the current health reminder information, such as news information items and health analysis items, can also be presented on the interactive interface, and then, the corresponding information content can be presented in response to the target user's triggering operation on the related items.

[0143] Continue to see Fig.11 When the target user triggers the information item, the introduction, manifestations and prevention of sub-health will be presented, so that the target user can obtain health tips and resolve doubts about the health tips at the same time.

[0144] See also Fig.12 FIG. 2 shows another interface schematic diagram for providing health reminder information according to an exemplary embodiment of the present disclosure. Fig.12 When the health monitoring information meets the preset warning conditions, health reminder information can be provided to the target user's terminal (including smart watches and smart phones) and to the terminals of the target user's associated users.

[0145] Among them, the health reminder information can also present related items related to the current health reminder information, such as sleep quality evaluation results, results of the third biometric characteristics, health monitoring information and corresponding preset thresholds, so that users can quickly obtain the key content of the reminder.

[0146] The disclosed embodiment simultaneously sends health reminder information to the terminals of the target user's associated users, and obtains the target user's health status through multiple parties, so as to remind, discover and urge the target user to pay attention to health issues.

[0147] Furthermore, in an exemplary embodiment, another method of providing health reminder information is provided. Fig.13 As shown, in response to the health monitoring information meeting the preset warning condition, providing health prompt information to the terminal associated with the target user may include steps S1310 and S1320:

[0148] Step S1310: Obtaining the location information of the target user within a predetermined period when the health monitoring information meets the preset warning condition.

[0149] The scheduled period can be a period of historical time starting from the current time. For example, if the current time is May 12, 2023, the scheduled period can be between May 1, 2023 and May 12, 2023. The location information of the target user within the scheduled period is obtained when the health monitoring information meets the preset warning conditions.

[0150] The location information may be obtained through positioning of the terminal corresponding to the target user.

[0151] Step S1320: If the duration of the location information being at the target location exceeds a set threshold, health reminder information and corresponding risk warning information are provided to the terminal associated with the target user.

[0152] Risk warning information is warning information used to indicate that the current health status of the target user is in a specific situation, for example, it can be warning information of the risk of infectious diseases, warning information of high health risks, etc. The target location can be a residence, a company, a hospital, or the target location can be more finely divided, such as the target location is the bathroom, kitchen, etc. in the residence of the target user. The embodiment of the present disclosure can determine the target location according to actual conditions.

[0153] Taking the target location as the residence of the target user as an example, when it is found that the location information of the target user's health detection information that meets the preset warning conditions is all located at the residence, health reminder information and corresponding risk warning information are provided to the terminal associated with the target user. In this case, the user has been at home for a long time and has health problems, so risk warning information can be provided to the associated terminal at the same time to warn the relevant users to pay special attention.

[0154] Taking the bathroom in the target user's home as an example, when it is found that the target user's health detection information meets the preset warning conditions, the location information is all located in the bathroom of the home. In this case, the target user may be at risk of related infectious diseases, such as malaria, accompanied by abdominal pain, nausea, diarrhea, etc. When sending health reminder information, risk warning information of "risk of infection" can be provided at the same time to enable related users to reduce unnecessary contact and reduce the transmission rate of infectious diseases.

[0155] It should be noted that the above examples are illustrative only. In the case where the duration of the target user's location information at the target location exceeds a predetermined threshold, the embodiment of the present disclosure adds risk warning information, increases attention to the health of the target user, and provides timely intervention and treatment, thereby reducing the risk of infection.

[0156] Fig.14 A complete flow chart of a health monitoring method according to an exemplary embodiment of the present disclosure is shown below. Fig.14 The health monitoring method of the embodiment of the present disclosure is described.

[0157] First, a first biometric feature and a second biometric feature are acquired based on wireless signal information of a scene where the target user is located.

[0158] The first biometric characteristic corresponds to the sleeping state, and the second sleeping characteristic corresponds to the awake state, such as the heart rate and breathing rate in the awake state. The first biometric characteristic at least includes the sleeping time, the deep sleeping time, and the breathing rate during the sleeping process.

[0159] Secondly, a sleep quality evaluation result of the target user is determined based on the first biometric feature.

[0160] The first biological characteristic is evaluated using a pre-trained sleep quality evaluation model to obtain a sleep quality evaluation result.

[0161] Next, a third biometric feature is obtained after the target user performs the target action, where the third biometric feature is used to reflect the biometric feature recovery capability of the target user after the target user performs the target action.

[0162] The target user may actively trigger the test to obtain the third biometric feature; or the third biometric feature may be obtained without the target user's awareness.

[0163] Furthermore, the health monitoring information is determined by combining the second biometric feature, the third biometric feature and the sleep quality evaluation result.

[0164] The second biometric characteristic, the third biometric characteristic and the sleep quality evaluation result are imported into a pre-trained health status evaluation model to obtain health monitoring information.

[0165] The detailed details involved in the above steps have been recorded in the above method embodiment and will not be repeated here.

[0166] Furthermore, it is determined whether the health monitoring information meets the preset warning conditions.

[0167] Among them, if the health monitoring information is greater than a preset threshold, health reminder information can be provided to the terminal associated with the target user.

[0168] Finally, it is determined whether the number of times the health monitoring information meets the preset warning conditions meets the preset number of times.

[0169] Among them, if the health monitoring information meets the preset warning conditions a certain number of times, health reminder information is provided to the terminal associated with the target user; otherwise, the physical condition of the target user continues to be monitored.

[0170] It should be noted that in the above steps, the execution subject may be the terminal corresponding to the target user; the execution subject may also be a server (such as a cloud), see Fig.15As shown, as an example but not limitation, the wearable device 1510 worn by the target user (such as the elderly) collects wireless signal information and sends the wireless signal information to the server 1520, so that the server 1520 performs the health monitoring information determination method of the embodiment of the present disclosure based on the wireless signal information to obtain health monitoring information. The server 1520 can continue to determine whether to trigger an early warning based on the health monitoring information, or the server 1520 can feed back the health monitoring information to the wearable device 1510, so that the wearable device 1510 can determine whether to trigger an early warning by itself.

[0171] When an early warning needs to be triggered, health reminder information can be provided to each terminal associated with the target user (such as wearable device 1510 and terminal device 1530) at the same time.

[0172] In the above process, the data processing part that occupies resources can be executed by the server, which has a fast calculation speed and reduces the data processing amount on the user side, thereby reducing energy consumption and storage.

[0173] In summary, the method for determining health monitoring information provided by the embodiment of the present disclosure, on the one hand, determines the sleep quality evaluation result of the target user based on the first biometric feature, realizes the imperceptible monitoring of the sleep quality of the target user, and takes the sleep quality as one of the factors affecting the health monitoring information. On the other hand, the third biometric feature after the target user performs the target action is obtained to realize the imperceptible monitoring of the target user's ability to recover life characteristics after performing the action. Considering that the life characteristic recovery level of users with potential health problems and healthy users after performing the same action is different, the life characteristic recovery ability (third biometric feature) is used as one of the factors affecting the health monitoring information, increasing the determination dimension of the health monitoring information and improving the accuracy of the health monitoring information; on the other hand, the health monitoring information is determined by combining the second biometric feature, the third biometric feature and the sleep quality evaluation result. The process combines the static health data (sleep state) and dynamic health data (after performing the target action) of the target user. Without increasing the hardware cost, the target user does not need to wear any additional equipment. It is a completely contactless health monitoring process, which can process the health data of the target user in time to realize early monitoring and early intervention of the health status of the target user and reduce the cost of health monitoring. In addition, it avoids the emotional tension of target users going to a dedicated testing section for health checkups, further improving the accuracy of health monitoring.

[0174] It should be noted that the above figures are only schematic illustrations of the processes included in the method according to the exemplary embodiments of the present disclosure, and are not intended to be limiting. It is easy to understand that the processes shown in the above figures do not indicate or limit the time sequence of these processes. In addition, it is also easy to understand that these processes can be performed synchronously or asynchronously, for example, in multiple modules.

[0175] For further reference, Fig.16 As shown, in an exemplary embodiment of the present disclosure, a health monitoring information determination device 1600 is provided, comprising a first feature acquisition module 1610, a first processing module 1620, a second feature acquisition module 1630, and a second processing module 1640. Among them:

[0176] The first feature acquisition module 1610 is used to acquire biometric features based on the wireless signal information of the scene in which the target user is located, and the biometric features include a first biometric feature corresponding to the sleeping state and a second biometric feature corresponding to the awake state; the first processing module 1620 is used to determine the sleep quality evaluation result of the target user based on the first biometric feature; the second feature acquisition module 1630 is used to acquire the third biometric feature of the target user after the target user performs the target action, and the third biometric feature is used to reflect the biometric recovery ability of the target user after the target user performs the target action; the second processing module 1640 is used to determine the health monitoring information in combination with the second biometric feature, the third biometric feature and the sleep quality evaluation result.

[0177] In an exemplary embodiment, the wireless signal information includes a WIFI signal, and the first feature acquisition module 1610 is configured to execute: acquiring channel state information corresponding to the target user in the WIFI environment according to the WIFI signal; and determining the biometric feature based on the channel state information.

[0178] In an exemplary embodiment, the first feature acquisition module 1610 is configured to perform: determining the biometric type; filtering the channel state information to obtain frequency band information corresponding to the frequency range of the biometric type; and determining the biometric based on the frequency band information.

[0179] In an exemplary embodiment, the first processing module 1620 is configured to execute: inputting the first biometric feature into a sleep quality evaluation model to obtain a sleep quality evaluation result; wherein the first biometric feature includes at least sleep duration, deep sleep duration and breathing frequency in the sleep state.

[0180] In an exemplary embodiment, the first processing module 1620 is configured to perform: inputting the first biometric feature into a sleep quality evaluation model to obtain a model output result; obtaining the historical sleep quality evaluation results of the target user, and determining the sleep quality evaluation result based on the historical sleep quality evaluation results and the model output result.

[0181] In an exemplary embodiment, the first processing module 1620 is further configured to execute: determining a sleep quality evaluation model from candidate sleep evaluation models according to the age group to which the target user belongs; wherein the candidate sleep evaluation model is obtained by training based on sleep sample data corresponding to the age group.

[0182] In an exemplary embodiment, the second feature acquisition module 1630 is configured to perform: based on wireless signal information, obtain the motion biometric characteristics of the target user after performing the target action; obtain the time required for the motion biometric characteristics to recover to a preset state; and determine the third biometric characteristic based on the time length.

[0183] In an exemplary embodiment, the second feature acquisition module 1630 is configured to perform: obtaining a correction weight corresponding to the target action, the correction weight being determined in advance based on the biometric recovery ability of a healthy user after performing actions of different types; and determining a third biometric feature based on the correction weight and duration.

[0184] In an exemplary embodiment, the health monitoring information determination device 1600 also includes a first determination module, which is configured to perform: in response to a test trigger operation, presenting candidate actions; in response to an action selection operation, determining the action corresponding to the action selection operation as a target action, and determining the action type of the target action.

[0185] In an exemplary embodiment, the health monitoring information determining device 1600 further includes a first determining module configured to determine the action type of the target action according to the wireless signal information.

[0186] In an exemplary embodiment, the second feature acquisition module 1630 is configured to perform: obtaining a distance value between the duration and a standard duration, where the standard duration is predetermined based on a biometric recovery duration of a healthy user after performing a target action; and determining a third biometric feature based on the distance value.

[0187] In an exemplary embodiment, the target user has multiple motion biometric features after performing the target action, and the second feature acquisition module 1630 is configured to acquire the duration corresponding to each motion biometric feature; and determine the third biometric feature in combination with the duration corresponding to each motion biometric feature.

[0188] In an exemplary embodiment, the second processing module 1640 is configured to execute: importing the second biometric characteristic, the third biometric characteristic and the sleep quality evaluation result into the health status evaluation model to obtain health monitoring information; wherein the second biometric characteristic includes at least the breathing rate and heart rate of the target user when the user is in an awake state.

[0189] In an exemplary embodiment, the health monitoring information determining device 1600 also includes a response module, which is configured to execute: in response to the health monitoring information satisfying a preset warning condition, providing health prompt information to a terminal associated with the target user.

[0190] In an exemplary embodiment, the response module is also configured to perform: obtaining the location information of the target user within a predetermined period when the health monitoring information meets the preset warning conditions; if the time length of time that the location information is at the target location exceeds a set threshold, providing health reminder information and corresponding risk warning information to the terminal associated with the target user.

[0191] The specific details of each module in the above device have been described in detail in the implementation method of the method part. The undisclosed details can be found in the implementation method of the method part, so they will not be repeated here.

[0192] The specific details of each module in the above device have been described in detail in the implementation method of the method part. The undisclosed details can be found in the implementation method of the method part, so they will not be repeated here.

[0193] Those skilled in the art will appreciate that various aspects of the present disclosure may be implemented as systems, methods or program products. Therefore, various aspects of the present disclosure may be specifically implemented in the following forms, namely: complete hardware implementation, complete software implementation (including firmware, microcode, etc.), or a combination of hardware and software, which may be collectively referred to herein as "circuits", "modules" or "systems".

[0194] The exemplary embodiments of the present disclosure also provide an electronic device for the above method, which may be the above imaging device or server. Generally, the electronic device includes at least a processor and a memory, the memory is used to store executable instructions of the processor, and the processor is configured to execute the above method by executing the executable instructions.

[0195] Below Fig.17 Taking the mobile terminal 1700 in the example, the structure of the electronic device in the embodiment of the present disclosure is exemplarily described. It should be understood by those skilled in the art that in addition to the components specifically used for mobile purposes, Fig.17 The structure in the figure can also be applied to fixed type devices. In other embodiments, the mobile terminal 1700 may include more or fewer components than shown in the figure, or combine some components, or split some components, or arrange the components differently. The components shown in the figure can be implemented in hardware, software, or a combination of software and hardware. The interface connection relationship between the components is only shown schematically and does not constitute a structural limitation of the mobile terminal 1700. In other embodiments, the mobile terminal may also adopt the same Fig.17 Different interface connection methods, or a combination of multiple interface connection methods.

[0196] See also Fig.17The mobile terminal 1700 includes a radio frequency (RF) circuit 1710, a memory 1720, an input unit 1730, a display unit 1740, a sensor 1750, an audio circuit 1760, a near field communication module 1770, a processor 1780, and a power supply 1790.

[0197] The RF circuit 1710 can be used for receiving and sending signals during the process of sending and receiving information or making calls. In particular, after receiving the downlink information of the base station, it is sent to the processor 1780 for processing; in addition, the designed uplink data is sent to the base station. Generally, the RF circuit includes but is not limited to an antenna, at least one amplifier, a transceiver, a coupler, a low noise amplifier (Low Noise Amplifier, LNA), a duplexer, etc. In addition, the RF circuit 1710 can also communicate with the network and other devices through wireless communication. The above-mentioned wireless communication can use any communication standard or protocol, including but not limited to the Global System of Mobile communication (Global System of Mobile communication, GSM), General Packet Radio Service (General Packet Radio Service, GPRS), Code Division Multiple Access (Code Division Multiple Access, CDMA), Wideband Code Division Multiple Access (Wideband Code Division Multiple Access, WCDMA), Long Term Evolution (Long Term Evolution, LTE)), email, Short Messaging Service (SMS), etc.

[0198] The memory 1720 can be used to store software programs and modules. The processor 1780 executes various functional applications and data processing of the mobile terminal by running the software programs and modules stored in the memory 1720, such as storing the received information in the memory 1720. The memory 1720 may mainly include a program storage area and a data storage area, wherein 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 according to the use of the mobile terminal (such as audio data, a phone book, etc.), etc., and the data storage area may also store data fed back by other terminals. In addition, the memory 1720 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, or other volatile solid-state storage devices.

[0199] The input unit 1730 may be used to receive input digital or character information, and to generate key signal input related to user settings and function control of the terminal 1700. Specifically, the input unit 1730 may include a touch panel 1731 and other input devices 1732. The touch panel 1731, also known as a touch screen, may collect user touch operations on or near it (such as operations performed by the user using a finger, stylus, or any other suitable object or accessory on or near the touch panel 1731), and drive corresponding connection devices according to a pre-set program.

[0200] The display unit 1740 can be used to display information input by the user or information provided to the user and various menus of the mobile terminal, such as outputting received health reminder information. The display unit 1740 may include a display panel 1741. Optionally, the display panel 1741 may be configured in the form of a liquid crystal display (Liquid Crystal Display, LCD), an organic light-emitting diode (Organic Light-Emitting Diode, OLED), etc. Further, the touch panel 1731 may cover the display panel 1741. When the touch panel 1731 detects a touch operation on or near it, it is transmitted to the processor 1780 to determine the type of touch event. Subsequently, the processor 1780 provides a corresponding visual output on the display panel 1741 according to the type of touch event. Although in Fig.17 In the embodiment, the touch panel 1731 and the display panel 1741 are used as two independent components to implement the input and output functions of the mobile terminal, but in some embodiments, the touch panel 1731 and the display panel 1741 can be integrated to implement the input and output functions of the mobile terminal.

[0201] The mobile terminal 1700 may also include at least one sensor 1750, such as a light sensor, a motion sensor, and other sensors. Specifically, the light sensor may include an ambient light sensor and a proximity sensor, wherein the ambient light sensor may adjust the brightness of the display panel 1741 according to the brightness of the ambient light, and the proximity sensor may turn off the display panel 1741 and / or the backlight when the mobile terminal is moved to the ear. As a type of motion sensor, the accelerometer sensor can detect the magnitude of acceleration in all directions (generally three axes), and can detect the magnitude and direction of gravity when stationary. It can be used for applications that identify the posture of the mobile terminal (such as horizontal and vertical screen switching, related games, magnetometer posture calibration), vibration recognition related functions (such as pedometer, tapping), etc.; as for other sensors that can be configured in the mobile terminal, such as gyroscopes, barometers, hygrometers, thermometers, infrared sensors, etc., they will not be repeated here.

[0202] The audio circuit 1760, the speaker 1761, and the microphone 1762 can provide an audio interface between the user and the mobile terminal. The audio circuit 1760 can transmit the electrical signal converted from the received audio data to the speaker 1761, which is converted into a sound signal for output; on the other hand, the microphone 1762 converts the collected sound signal into an electrical signal, which is received by the audio circuit 1760 and converted into audio data, and then the audio data is output to the processor 1780 for processing, and then sent to another mobile terminal through the RF circuit 110, or the audio data is output to the memory 1720 for further processing. For example, the mobile terminal can play health reminder information through the audio circuit 1760 and notify the user by voice signal.

[0203] The near field communication module 1770 is integrated with a Bluetooth communication module, and establishes a communication connection with the wearable device through the Bluetooth communication module, and receives health reminder information or biometric features fed back by the wearable device. Fig.17 A near field communication module 1770 is shown, but it is understandable that it is not an essential component of the mobile terminal 1700 and can be omitted as needed without changing the essence of the application.

[0204] The processor 1780 is the control center of the mobile terminal. It uses various interfaces and lines to connect various parts of the entire mobile terminal. By running or executing software programs and / or modules stored in the memory 1720 and calling data stored in the memory 1720, it executes various functions of the mobile terminal and processes data, thereby monitoring the mobile terminal as a whole. Optionally, the processor 1780 may include one or more processing units; preferably, the processor 1780 may integrate an application processor and a modem processor, wherein the application processor mainly processes the operating system, user interface, and application programs, and the modem processor mainly processes wireless communications. It is understandable that the above-mentioned modem processor may not be integrated into the processor 1780.

[0205] The mobile terminal 1700 also includes a power supply 1790 (such as a battery) for supplying power to various components. Preferably, the power supply can be logically connected to the processor 1780 through a power management system, so that the power management system can manage functions such as charging, discharging, and power consumption.

[0206] In addition, the exemplary embodiments of the present disclosure further provide a computer-readable storage medium on which a program product capable of implementing the above-mentioned method of the present specification is stored. In some possible implementations, various aspects of the present disclosure may also be implemented in the form of a program product, which includes a program code, and when the program product is run on a terminal device, the program code is used to enable the terminal device to execute the steps according to various exemplary embodiments of the present disclosure described in the above-mentioned "Exemplary Method" section of the present specification.

[0207] It should be noted that the computer-readable medium shown in the present disclosure may be a computer-readable signal medium or a computer-readable storage medium or any combination of the above two. The computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above.

[0208] In the present disclosure, a computer-readable storage medium may be any tangible medium containing or storing a program that may be used by or in combination with an instruction execution system, apparatus, or device. In the present disclosure, a computer-readable signal medium may include a data signal propagated in a baseband or as part of a carrier wave, which carries a computer-readable program code. Such propagated data signals may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. A computer-readable signal medium may also be any computer-readable medium other than a computer-readable storage medium, which may send, propagate, or transmit a program for use by or in combination with an instruction execution system, apparatus, or device. The program code contained on the computer-readable medium may be transmitted using any suitable medium, including but not limited to: wireless, wire, optical cable, RF, etc., or any suitable combination of the above.

[0209] In addition, program code for performing the operations of the present disclosure may be written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Java, C++, etc., and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user computing device, partially on the user device, as a separate software package, partially on the user computing device and partially on a remote computing device, or entirely on a remote computing device or server. In cases involving a remote computing device, the remote computing device may be connected to the user computing device through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computing device (e.g., through the Internet using an Internet service provider).

[0210] Other embodiments of the present disclosure will be readily apparent to those skilled in the art after considering the specification and practicing the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of the present disclosure that follow the general principles of the present disclosure and include common knowledge or customary technical means in the art that are not disclosed in the present disclosure. The specification and embodiments are to be considered merely as exemplary, and the true scope and spirit of the present disclosure are indicated by the claims.

Claims

1. A method for determining health monitoring information, characterized in that: include: Acquire biometric features according to wireless signal information of a scene where the target user is located, wherein the biometric features include a first biometric feature corresponding to a sleeping state and a second biometric feature corresponding to a non-sleeping state; Determine a sleep quality evaluation result of the target user based on the first biometric feature; Acquire a third biometric feature after the target user performs the target action, where the third biometric feature is used to reflect the biometric feature recovery capability of the target user after the target user performs the target action; The health monitoring information is determined by combining the second biometric feature, the third biometric feature and the sleep quality evaluation result.

2. The method according to claim 1, characterized in that: The wireless signal information includes a WIFI signal, and the acquiring of biometric features according to the wireless signal information of the scene where the target user is located includes: Acquire channel state information corresponding to the target user in the WIFI environment according to the WIFI signal; The biometric characteristic is determined based on the channel state information.

3. The method according to claim 2, characterized in that The determining the biometric feature based on the channel state information comprises: Determine the biometric type; Performing filtering processing on the channel state information to obtain frequency band information corresponding to the frequency range of the biometric feature type; The biometric feature is determined based on the frequency band information.

4. The method according to claim 1, characterized in that: The determining the sleep quality evaluation result of the target user based on the first biometric feature includes: The first biometric characteristic is input into a sleep quality evaluation model to obtain the sleep quality evaluation result; wherein the first biometric characteristic at least includes sleep duration, deep sleep duration and breathing frequency in the sleep state.

5. The method according to claim 4, characterized in that The step of inputting the first biometric feature into a sleep quality evaluation model to obtain the sleep quality evaluation result includes: Inputting the first biometric feature into a sleep quality evaluation model to obtain a model output result; Acquire historical sleep quality evaluation results of the target user, and determine the sleep quality evaluation result according to the historical sleep quality evaluation results and the model output result.

6. The method according to claim 4, characterized in that Before inputting the first biometric feature into the sleep quality evaluation model to obtain the sleep quality evaluation result, the method further includes: Determining the sleep quality evaluation model from candidate sleep evaluation models according to the age group to which the target user belongs; The candidate sleep evaluation model is obtained by training based on the sleep sample data corresponding to the age level.

7. The method according to claim 1, characterized in that The obtaining of a third biometric feature of the target user after the target user performs the target action includes: Based on the wireless signal information, obtaining the motion biometric characteristics of the target user after performing the target action; Obtaining the time required for the motion biometric feature to return to a preset state; The third biometric characteristic is determined based on the duration.

8. The method according to claim 7, characterized in that The determining the third biometric feature based on the duration includes: Obtaining a correction weight corresponding to the target action, wherein the correction weight is determined in advance based on a biometric recovery ability of a healthy user after performing actions of different action types; The third biometric feature is determined according to the modified weight and the duration.

9. The method according to claim 8, characterized in that Before determining the third biometric feature based on the duration, the method further includes: In response to the test triggering operation, presenting candidate actions; In response to an action selection operation, the action corresponding to the action selection operation is determined as the target action, and the action type of the target action is determined.

10. The method according to claim 8, characterized in that Before determining the third biometric feature based on the duration, the method further includes: The action type of the target action is determined according to the wireless signal information.

11. The method according to claim 7, characterized in that The determining the third biometric feature based on the duration includes: Obtaining a distance value between the duration and a standard duration, where the standard duration is predetermined based on a biometric recovery duration of a healthy user after performing the target action; The third biometric characteristic is determined based on the distance value.

12. The method according to claim 7, characterized in that There are multiple motion biometric features of the target user after the target action is performed, and the duration corresponding to each of the motion biometric features is obtained; The determining the third biometric feature based on the duration includes: The third biometric feature is determined by combining the durations corresponding to the various motion biometric features.

13. The method according to claim 1, characterized in that The determining of health monitoring information by combining the second biometric feature, the third biometric feature and the sleep quality evaluation result includes: Importing the second biometric feature, the third biometric feature and the sleep quality evaluation result into a health status evaluation model to obtain the health monitoring information; The second biometric feature at least includes the breathing frequency and the heart rate of the target user when the target user is in the awake state.

14. The method according to any one of claims 1 to 13, characterized in that The method further comprises: In response to the health monitoring information satisfying a preset warning condition, health reminder information is provided to a terminal associated with the target user.

15. The method according to claim 14, characterized in that In response to the health monitoring information satisfying a preset warning condition, providing health prompt information to a terminal associated with the target user, further comprising: Obtaining the location information of the target user within a predetermined period when the health monitoring information meets the preset warning condition; If the duration that the location information is at the target location exceeds a set threshold, health reminder information and corresponding risk warning information are provided to the terminal associated with the target user.

16. A device for determining health monitoring information, characterized in that: include: A first feature acquisition module, used to acquire biometric features according to wireless signal information of a scene where the target user is located, wherein the biometric features include a first biometric feature corresponding to a sleeping state and a second biometric feature corresponding to a non-sleeping state; A first processing module, configured to determine a sleep quality evaluation result of the target user based on the first biometric feature; A second feature acquisition module is used to acquire a third biometric feature after the target user performs the target action, wherein the third biometric feature is used to reflect the biometric feature recovery ability of the target user after performing the target action; The second processing module is used to determine health monitoring information by combining the second biological feature, the third biological feature and the sleep quality evaluation result.

17. An electronic device, characterized in that: include: processor; as well as A memory, configured to store executable instructions of the processor; The processor is configured to perform the method of any one of claims 1 to 15 by executing the executable instructions.

18. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the method according to any one of claims 1 to 15 is implemented.

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