CN119453920A

CN119453920A - Health monitoring information determination method and device, electronic device and storage medium

Info

Publication number: CN119453920A
Application number: CN202310969243.5A
Authority: CN
Inventors: 林峰
Original assignee: Weiguang Co ltd
Current assignee: Weiguang Co ltd
Priority date: 2023-08-02
Filing date: 2023-08-02
Publication date: 2025-02-18

Abstract

The present disclosure provides a method and device for determining health monitoring information, an electronic device, and a computer-readable storage medium, and relates to the technical field of life feature recognition. The method for determining health monitoring information includes: obtaining biometric features according to 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; determining the sleep quality evaluation result of the target user based on the first biometric feature; obtaining a third biometric feature 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 action is performed; and determining health monitoring information in combination with the second biometric feature, the third biometric feature, and the sleep quality evaluation result. The present disclosure can facilitate and timely process the user's health data to remind and rescue the user.

Description

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

Technical Field

The present disclosure relates to the technical field of vital sign recognition, and in particular, to a health monitoring information determining method, a health monitoring information determining apparatus, an electronic device, and a computer-readable storage medium.

Background

With social development and technological progress, fast-paced life has an influence on human health. For example, the number of people in sub-health is gradually increased, and the long-term sub-health is very unfavorable for human health. It is particularly important how to monitor and conduct early interventions on the population with potential health threats.

In the related art, a user is required to wear a special device for health detection, the device is expensive and inconvenient to operate, and the user can respond to abnormal conditions only when obvious abnormality occurs to the user, but the treatment opportunity may be missed, so that the health of the user is affected.

Disclosure of Invention

The disclosure aims to provide a health monitoring information determining method, a health monitoring information determining device, electronic equipment and a computer readable storage medium, so that health data of a user can be conveniently and timely processed at least to a certain extent, and reminding and rescuing can be carried out on the user.

According to a first aspect of the disclosure, a health monitoring information determining method is provided, which includes acquiring biological characteristics according to wireless signal information of a scene where a target user is located, wherein the biological characteristics include a first biological characteristic corresponding to a sleep state and a second biological characteristic corresponding to an un-sleep state, determining a sleep quality evaluation result of the target user based on the first biological characteristic, acquiring a third biological characteristic of the target user after the target user performs a target action, wherein the third biological characteristic is used for reflecting biological characteristic recovery capability of the target user after the target user performs the target action, and determining health monitoring information by combining the second biological characteristic, the third biological characteristic and the sleep quality evaluation result.

According to a second aspect of the disclosure, a health monitoring information determining device is provided, which comprises a first feature acquisition module, a first processing module and a second processing module, wherein the first feature acquisition module is used for acquiring biological features according to wireless signal information of a scene where a target user is located, the biological features comprise a first biological feature corresponding to a sleep state and a second biological feature corresponding to an unmeshed state, the first processing module is used for determining a sleep quality evaluation result of the target user based on the first biological features, the second feature acquisition module is used for acquiring a third biological feature after the target user performs a target action, the third biological feature is used for reflecting biological feature restoration capability of the target user after the target user performs the target action, and the second processing module is used for determining health monitoring information by combining the second biological feature, the third biological feature and the sleep quality evaluation result.

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 executed by the one or more processors cause the one or more processors to implement the method described above.

According to a fourth aspect of the present disclosure, there is provided a computer readable storage medium having stored thereon a computer program which, when executed by a processor, implements the method described above.

According to the method for determining the health monitoring information, on one hand, the first biological characteristic corresponding to the sleep state and the second biological characteristic corresponding to the non-sleep state are obtained through the wireless signal information of the scene where the target user is located, which is received by the terminal equipment, the sleep quality evaluation result of the target user is determined based on the first biological characteristic, the non-perception monitoring of the sleep quality of the target user is achieved, the sleep quality is taken as one factor affecting the health monitoring information, on the other hand, the third biological characteristic of the target user after the target user performs the target action is obtained, the non-perception monitoring of the life characteristic recovery capability of the target user after the target user performs the action is achieved, the life characteristic recovery capability (third biological characteristic) of the user with potential health problems is taken as one factor affecting the health monitoring information in consideration of different life characteristic recovery levels of the user after the same action is performed, the accuracy of the health monitoring information is improved, on the other hand, the health monitoring information is determined by combining the second biological characteristic, the third biological characteristic and the sleep quality evaluation result, the health monitoring information is combined, static health data (sleep state) and dynamic health data (target state) of the target user are combined, the cost of the target user is not required to be increased, the health monitoring cost of the user is reduced, and the health monitoring process is completely required to be carried out in real time, and the health monitoring process is carried out by the user, and the health monitoring process is not required to be completely, and the health monitoring process has the cost is reduced.

It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the disclosure.

Drawings

The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the disclosure and together with the description, serve to explain the principles of the disclosure. It will be apparent to those of ordinary skill in the art that the drawings in the following description are merely examples of the disclosure and that other drawings may be derived from them without undue effort. In the drawings:

Fig. 1 illustrates a health monitoring information determination system diagram related to a health monitoring information determination method of an embodiment of the present disclosure;

FIG. 2 schematically illustrates a flow chart of a method of health monitoring information determination according to an exemplary embodiment of the present disclosure;

FIG. 3 schematically illustrates a flowchart of one implementation of acquiring a biometric feature from wireless signal information in accordance with an exemplary embodiment of the present disclosure;

fig. 4 schematically illustrates a diagram of decomposing channel state information in an exemplary embodiment of the present disclosure;

fig. 5 schematically illustrates a schematic diagram before and after filtering channel state information in an exemplary embodiment of the present disclosure;

FIG. 6 schematically illustrates a flowchart of another implementation of determining sleep quality assessment results for a target user in an exemplary embodiment of the present disclosure;

FIG. 7 schematically illustrates a flowchart of one implementation of acquiring a third biometric feature in accordance with an exemplary embodiment of the present disclosure;

FIG. 8 schematically illustrates another manner of determining a third biometric feature in an exemplary embodiment of the present disclosure;

FIG. 9 schematically illustrates a schematic diagram of an interactive interface diagram in an exemplary embodiment of the present disclosure;

FIG. 10 schematically illustrates a schematic diagram of acquiring a motion biometric in an exemplary embodiment of the present disclosure;

FIG. 11 schematically illustrates an interface diagram for providing health cue information in an exemplary embodiment of the present disclosure;

FIG. 12 schematically illustrates another interface diagram for providing health cue information in an exemplary embodiment of the present disclosure;

FIG. 13 schematically illustrates a flowchart of another manner of providing health cue information in an exemplary embodiment of the present disclosure;

FIG. 14 schematically illustrates a complete flow chart of a method of health monitoring in an exemplary embodiment of the present disclosure;

FIG. 15 schematically illustrates an interface diagram for presenting hints information in an exemplary embodiment of the disclosure;

Fig. 16 schematically illustrates a structural diagram of a health monitoring information determining apparatus in an exemplary embodiment of the present disclosure;

fig. 17 schematically shows a schematic diagram of an electronic device to which embodiments of the present disclosure may be applied.

Detailed Description

Example embodiments will now be described more fully with reference to the accompanying drawings. However, the exemplary embodiments may be embodied in many forms and should not be construed as limited to the examples set forth herein, but rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the concept of the exemplary 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.

Furthermore, the drawings are merely schematic illustrations of the present disclosure and are not necessarily drawn to scale. The same reference numerals in the drawings denote the same or similar parts, and thus a repetitive description thereof will be omitted. Some of the block diagrams shown in the figures are functional entities and do not necessarily correspond to physically or logically separate entities. These functional entities may be implemented in software or in one or more hardware modules or integrated circuits or in different networks and/or processor devices and/or microcontroller devices.

Fig. 1 illustrates a health monitoring information determination system diagram related to a health monitoring information determination method according to an embodiment of the present disclosure. As shown in fig. 1, the system includes a signal transmitting device Tx (e.g., a WIFI wireless router) and a signal receiving device Rx, each of which has two or more receiving antennas. The signal transmitting device Tx transmits a wireless signal, and the signal receiving device Rx receives wireless information and collects the wireless signal information.

When the monitored target user exists in the wireless environment, the presence of the target user can cause the change on the wireless signal, for example, the respiration of the target user can cause the weak change of the wireless signal, and the purpose of monitoring the health state of the target user can be realized by collecting the wireless signal information.

In the embodiment of the disclosure, the provided health monitoring information determining method can be executed by terminal equipment, the terminal equipment is used as signal receiving equipment, a first biological characteristic corresponding to a sleep state and a second biological characteristic corresponding to a non-sleep state are obtained according to wireless signal information of a scene where a target user is located, a sleep evaluation result of the target user is determined based on the first biological characteristic, a third biological characteristic after the target user executes a target action is obtained, and then the second biological characteristic, the third biological characteristic and sleep quality evaluation result health monitoring information are combined. In the case that all steps in the health monitoring information determining method provided by the embodiment of the present disclosure may be performed by the terminal device, all steps may be performed by the terminal device processor.

The terminal device may be an intelligent device with a data processing function, for example, may be an intelligent device such as a smart phone, a computer, a tablet computer, a vehicle-mounted device, a wearable device, a monitoring device, and the terminal device may also be referred to as a mobile terminal, a mobile device, and the like.

Furthermore, the health monitoring information determining method provided by the embodiment of the present disclosure may also be executed by a server. Correspondingly, in this manner performed by the server, the server may initiate execution of steps in the technical solutions of embodiments of the present disclosure in response to a trigger execution, which may be sent by the terminal device used by the user, or may be triggered locally by the server in response to some automation event. The server may receive the wireless signal information sent by the terminal device, and further execute the steps of the embodiments of the present disclosure.

The server may be a background system for providing related services in embodiments of the present disclosure, and may include a cluster formed by one or more electronic devices having a computing function, such as a portable computer, a desktop computer, and a smart phone.

In addition, the technical scheme of the embodiment of the disclosure can be cooperatively executed by the terminal equipment and the server. In this manner, which is cooperatively performed by the electronic device and the server, in this manner, according to the embodiments of the present disclosure, part of the steps in the technical solution provided in the embodiments of the present disclosure are performed by the terminal device, and the other part of the steps are performed by the server. For example, the technical scheme provided by the embodiment of the disclosure may be that the server obtains the biological characteristics according to the wireless signal information of the scene where the target user is located, sends the biological characteristics to the server, determines the sleep quality evaluation result of the target user based on the first biological characteristics by the server, and determines the health monitoring information by combining the second biological characteristics, the third biological characteristics and the sleep quality evaluation result. The server may also send the health monitoring information to the terminal device associated with the target user.

In this way, the steps performed by the terminal device and the server, respectively, may be dynamically adjusted according to the actual situation, and are not particularly limited.

In the embodiments of the present disclosure, an example is described in which a technical scheme is executed by a terminal device.

The current population with potential health threats is growing, for example, people who are in sub-health state for a long time often check or take measures when symptoms are obvious, and the best treatment opportunity can be missed, and even life safety is threatened. In many cases the body has already given relevant problem signals, but is not sufficiently focused and alert.

In the related art, the magnetic oscillation principle is used for detecting the magnetic field frequency of a human body to calculate the fatigue degree of the human body, when the fatigue value is in a normal state within a range of 60 to 80, the fatigue value is less than 60 and is excessive fatigue, and when the fatigue value is 80, the fatigue value is long-term fatigue, but the method has insufficient accuracy and stability.

Either the user goes to medical examinations only when a significant anomaly is present or requires expensive additional equipment to be used to check, which is typically responsive to anomalies when a significant anomaly is present by the user, in which case the user would miss the opportunity for early intervention, affecting the user's health.

Based on one or more of the above-mentioned problems, an embodiment of the present disclosure provides a method capable of timely processing user health data, and normalizes health monitoring to achieve the purpose of health reminding and rescue for a user. According to the embodiment of the disclosure, the health monitoring information is obtained by timely processing the health data of the target user, and then the health monitoring information is utilized to monitor the health of the target user.

In the embodiment of the disclosure, the health monitoring information determining method can be applied to relevant scenes of body health monitoring of daily users. For example, the method steps of the embodiment of the disclosure are executed through the terminal device of the user to realize daily health monitoring, and for another example, for a group (such as solitary old people) needing special attention to the physical state, the health monitoring result can be determined through the method for determining the health monitoring information of the embodiment of the disclosure and sent to the associated terminal device, so that the guardian (such as a child) can timely know the physical state of the old people, and early intervention is performed on the potential health threat.

Furthermore, the health monitoring method of the embodiment of the disclosure can also be applied to the scene of health monitoring of users in related health institutions or communities. For example, daily health monitoring is achieved by implementing the method steps of the embodiments of the present disclosure in a hospital or care facility to guide relevant personnel for work navigation, early warning, etc. Referring to fig. 2, the health monitoring information determining method of the embodiment of the present disclosure may include the following steps S210 to S240:

in step S210, a biometric characteristic is obtained according to the wireless signal information of the scene in which the target user is located, where the biometric characteristic includes a first biometric characteristic corresponding to a sleep state and a second biometric characteristic corresponding to an unmeshed state.

In an exemplary embodiment of the present disclosure, the scenario in which the target user is located refers to a wireless environment scenario in which the target user is in the health monitoring information determining system, and the presence of the target user causes a change in wireless signal information received by the terminal device. The biometric may be relevant biometric information that can reflect the physical state of the target user, such as the breathing rate, heart beat frequency, sleep duration, breathing conditions during sleep, etc. of the target user. The biometric feature may also be related information obtained through statistics, which can reflect the physical state of the target user, for example, a period of time for which the respiratory rate of the target user returns to the normal frequency after performing a certain action, a period of time for which the heart rate returns to the normal heart rate after performing a certain action, and the like.

The first biological characteristic corresponding to the sleep state is a biological characteristic of the target user in the sleep state, which is acquired based on a wireless signal of a scene where the target user is located, such as sleep duration, respiratory rate during sleep, and the like, and the first biological characteristic is static health data of the target user. The second biological feature corresponding to the non-sleeping state refers to a biological feature acquired based on a wireless signal of a scene where the target user is located when the target user is not in the sleeping state, such as a respiratory rate, a heart rate and the like when the target user is not sleeping.

The wireless signal of the scene where the target user is located may be any one selected from WIFI signal, FMCW (Frequency Modulated Continuous Wave ) signal, UWB (Ultra Wide Band) signal, bluetooth, ultrasonic wave, etc. The following disclosure embodiments take a wireless signal as a WIFI signal as an example.

And acquiring the wireless signal information of the target user in the wireless signal scene to acquire the first biological characteristic and the second biological characteristic corresponding to the target user. It should be noted that the first biological feature and the second biological feature may be collected in real time without perception by the user, or may be collected at intervals of a preset period, and may be set accordingly according to the user's requirement.

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

In exemplary embodiments of the present disclosure, the physical state of the target user may be reflected to some extent in the quality of sleep. The quality of sleep can be judged by the sleep time, or the quality of sleep can be judged by comparing the currently determined sleep quality with the historical sleep quality of the target user according to the comparison result.

The sleep quality evaluation result of the target user can be determined through the first biological characteristic acquired under the condition that the target user is in the sleep state. For example, if the first biological features include sleep duration, deep sleep duration, respiratory rate during sleep, heart rate, etc., the sleep quality evaluation result may be determined in combination with the first biological features.

In step S230, a third biometric characteristic of the target user after the target user has performed the target action is obtained, where the third biometric characteristic is used to reflect the biometric characteristic recovery capability of the target user after the target user has performed the target action.

In the exemplary embodiment of the present disclosure, the target action may be a preset designated action, or a custom action of the target user according to the own needs, or a random action performed in daily life of the target user. Such as rope skipping, sit-ups, in-situ jumping, stair climbing, running, etc., are not particularly limited. The biometric recovery capability refers to the length of time required for the target user to recover his biometric to normal (standard of healthy human body) after the target user has performed the target action.

In some possible embodiments, only one athletic biometric (e.g., heart rate) may be selected as a dimensional feature for determining a third biometric, and in other possible embodiments, at least two athletic biometric (e.g., heart rate, respiratory rate) may be selected as a dimensional feature for determining a third biometric, increasing the accuracy and reliability of the third biometric by increasing the dimension of the athletic biometric.

In some possible embodiments, the duration of the target action performed by the target user may be limited, that is, the third biometric feature may be obtained after the target action with the preset duration is performed, so as to avoid affecting the accuracy of the detection result due to different movement durations of different users.

Since the performance of the population with potential health problems is not very different from the healthy population under normal conditions (e.g. no exercise), there is a difference in the response and recovery of the two populations after some actions are performed. For example, if ten push-ups are made simultaneously, a healthy user's heart rate may quickly return to normal levels, but a user with potential health threats, such as chronic and sub-healthy, may require a longer recovery time. According to the embodiment of the disclosure, through the third biological feature of the target user after the target action is executed, the biological feature recovery capability of the target user after the target action is executed is used as one of factors for determining the health monitoring information, potential health problems of the target user are easier to mine, and the accuracy of the health monitoring information is further improved.

In step S240, health monitoring information is determined in combination with the second biometric feature, the third biometric feature, and the sleep quality evaluation result.

In an exemplary embodiment of the present disclosure, the health monitoring information is an indicator that evaluates whether the target user has a potential health problem. For example, when the health monitoring information of the target user is higher than a preset standard, determining that the target user has a potential health problem. For another example, when the health monitoring information is at a preset health level, it is determined that the target user has a potential health problem.

The second biological characteristic and the sleep quality evaluation result are used as static health data of the target user, the third biological characteristic is used as dynamic health data of the target user, and the health monitoring information of the target user is comprehensively determined by combining the second biological characteristic, the third biological characteristic and the sleep quality evaluation result.

According to the method for determining the health monitoring information, on one hand, the sleep quality evaluation result of the target user is determined based on the first biological characteristics, the non-perception monitoring of the sleep quality of the target user is achieved, the sleep quality is taken as one of factors affecting the health monitoring information, on the other hand, the third biological characteristics of the target user after the target user performs the target action are obtained, the non-perception monitoring of the life characteristic recovery capability of the target user after the target user performs the action is achieved, the life characteristic recovery capability (third biological characteristics) is taken as one of factors affecting the health monitoring information in consideration of the fact that the life characteristic recovery level of a user with potential health problems is different from that of the life characteristic recovery level of the health user after the user performs the same action, the determination dimension of the health monitoring information is increased, the accuracy of the health monitoring information is improved, on the other hand, the second biological characteristics, the third biological characteristics and the sleep quality evaluation result are combined, the health monitoring information is determined, the static health data (sleep state) and the dynamic health data (after the target action) of the target user are combined, and any additional equipment is not required to be worn by the target user under the condition that the condition of not increasing hardware cost is required, the fact that the target user is completely non-contact health monitoring process is achieved, the health condition can be processed, the health condition of the target user can be monitored in time, the health condition of the target user can be monitored in time, and the health condition of the user is reduced, and the health condition of the health condition is monitored in time and the health condition is reduced.

In an exemplary embodiment, an implementation of acquiring a biometric feature from wireless signal information is provided. As shown in fig. 3, the wireless signal information may include a WIFI signal, and the step of obtaining the biometric feature according to the wireless signal information of the scene where the target user is located may include step S310 and step S320:

And step S310, obtaining channel state information corresponding to the WIFI environment of the target user according to the WIFI signal.

Referring to the system diagram shown in fig. 1, after the terminal device is linked with the wireless WIFI router, the wireless WIFI router feeds back Channel State Information (CSI) to the terminal device, so that the terminal device acquires the channel state Information corresponding to the target user.

CSI may describe the attenuation and phase shift experienced by WIFI signals during propagation, and the measured value of CSI may be changed by the biological characteristics of the human body, for example, the measured value of CSI may be changed in quasi-period due to thoracic cavity fluctuation caused by respiration of the human body.

Step S320 is to determine a biometric feature based on the channel state information.

In order to accurately obtain the biological characteristics of the target user from the channel state information, the channel state information can be processed in a filtering mode.

In an exemplary embodiment, a schematic diagram of decomposing channel state information according to an exemplary embodiment of the present disclosure is shown in fig. 4, and the process may include steps S410 to S430:

In step S410, a biometric type is determined.

Different biological characteristics need to adopt corresponding filtering modes, for example, the breathing rate of a person is between 10 and 40bmp, namely, the breathing rate is between 0.1667 and 0.677Hz, the heartbeat frequency is between 60 and 100 times per minute, and the heartbeat frequency is between about 1.25 and 1.42Hz. To extract the corresponding biometric feature from the CSI, the biometric feature type and its corresponding frequency range are determined.

Step S420, filtering the channel state information to obtain frequency band information corresponding to the frequency range of the biological characteristic type.

And determining a filtering mode adopted according to the frequency range of the biological characteristic type, and if a matched filter is selected for filtering, obtaining the frequency band information corresponding to the frequency range of the biological characteristic type. That is, only signals of a frequency band corresponding to the frequency range of the biometric type are retained, excluding background noise.

Fig. 5 shows a schematic diagram before and after filtering channel state information according to an exemplary embodiment of the present disclosure. The channel state information is filtered to obtain the frequency band information of the human body mutual communication frequency and the frequency information of the human body heartbeat.

Moreover, for the detection of the sleeping time length and the deep sleeping time length of the target user in the sleeping state, brain wave signals in the sleeping state or the deep sleeping state of the human body can be obtained, and the channel state information is filtered based on the frequency range corresponding to the brain wave signals to obtain the frequency band information in the sleeping state or the deep sleeping state.

Step S430, determining biological characteristics based on the frequency band information.

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

Taking the respiration rate determination as an example, firstly, an FFT (Fast Fourier Transform ) may be used to convert the respiration signal into frequency, calculate a dual-side amplitude spectrum, and obtain a single-side amplitude spectrum based on the dual-side amplitude spectrum, so as to determine the frequency corresponding to the peak value of the single-side amplitude spectrum as the respiration frequency of the target user.

Taking the sleep time as an example, the electroencephalogram signals generated in the sleep process are processed to divide the electroencephalogram signals into different sleep stages, and the time of each sleep stage is counted.

It should be noted that, the embodiments of the present disclosure may also calculate each biometric feature in other manners based on the frequency band information, which is not limited in particular.

According to the embodiment of the disclosure, the biological characteristics are obtained according to the wireless signal information of the scene where the target user is located, the existing sensor and WIFI chip on the terminal equipment (such as a mobile phone, a computer and wearable equipment) of the target user can be utilized, and the wireless WIFI router is combined, so that additional equipment is not required to be introduced, and the hardware cost is not increased. And moreover, the target user is prevented from wearing additional equipment, a non-contact monitoring mode is realized, the tension of the target user is further reduced, and the problem of inaccurate monitoring results caused by the emotion of the user is avoided.

In an exemplary embodiment, an implementation of determining sleep quality assessment results for a target user is provided. Determining the sleep quality assessment result of the target user based on the first biometric characteristic may include:

Inputting the first biological characteristic into a sleep quality evaluation model to obtain a sleep quality evaluation result, wherein the first biological characteristic at least comprises sleep duration, deep sleep duration and respiratory frequency in a sleep state.

The first biological feature of the embodiment of the present disclosure may further include a posture type, a posture change number, and the like in a sleep state, which may be adaptively adjusted according to actual requirements, which is not particularly limited.

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

The sleep-related data are used as training sample data, such as a user sample, a corresponding sleep duration, a deep sleep duration, a sleeping respiratory rate and the like, and the training sample data are input into a model to be trained for training. The model to be trained can be any model meeting the requirements, such as a classification model, and the like, and is not particularly limited.

In some possible embodiments, sleep quality assessment models corresponding to different age levels may also be trained separately based on sample data of the different age levels. For example, the ages of the users can be classified 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 is trained by using training sample data of each age level.

Based on the above, a corresponding sleep quality evaluation model can be determined from the candidate sleep evaluation models according to the age level to which the target user belongs, and the first biological characteristic is input, so that a corresponding sleep quality evaluation result is obtained.

As the user of different age levels increases with age, the sleep time length starts to decrease, which accords with biological laws and is not caused by potential physical health factors, and the obtained sleep quality evaluation result is only related to the physical state of the target user by inputting the first biological characteristics into the sleep quality model of the age level, which accords with the target user, so that the influence of natural age is eliminated.

In an exemplary embodiment, another implementation of determining the sleep quality assessment results of the target user is also provided. As shown in fig. 6, inputting the first biological feature into the sleep quality evaluation model, obtaining the sleep quality evaluation result may include step S610 and step S620:

step S610, inputting the first biological characteristic into a sleep quality evaluation model to obtain a model output result, and step S620, obtaining a historical sleep quality evaluation result of the target user, and determining the sleep quality evaluation result according to the historical sleep quality evaluation result and the model output result.

The historical sleep quality evaluation result may be a mean value of sleep quality evaluation results of the target user in a preset time period, may be a highest value of sleep quality evaluation results of the target user in the preset time period, may also be a previous sleep quality evaluation result of the target user in the current detection, and may be selected according to actual conditions, which is not particularly limited.

In order to enable the sleep quality evaluation result to truly reflect the physical state change of the target user, the sleep quality evaluation result obtained by combining the current model output result and the historical sleep quality evaluation result of the target user is used for determining the final sleep quality evaluation result through transverse comparison with the sleep quality of the target user, so that the accuracy and the reliability of the sleep quality evaluation are improved.

In some possible embodiments, the historical sleep quality evaluation result and the model output result may be taken as a difference value, and the difference value is used as a sleep quality evaluation result, so that the sleep quality change of the target user is reflected by the sleep quality evaluation result and is used as one of the supervision factors of the health state.

In an exemplary embodiment, an implementation of acquiring a third biometric feature is provided. As shown in fig. 7, acquiring the third biometric characteristic of the target user after the target user has performed the target action may include steps S710 to S730:

step S710, based on the wireless signal information, acquiring the movement biological characteristics of the target user after the target action is executed.

The exercise biometric is a biometric of the target user after performing the target action, for example, heart rate, respiratory rate, etc. after the target user has completed ten sit-ups.

The detailed process of acquiring the exercise biological feature based on the wireless signal can be referred to in steps S410 to S430, which are not described herein.

Step 720, obtaining the time required for restoring the exercise biological characteristics to the preset state.

The preset state may be a normal standard state corresponding to the exercise biometric feature, such as heart rate, respiratory rate, etc. in the non-exercise state. The relevant biological characteristics of the target user in the non-motion state can be collected in advance to serve as a preset state, and the state of the biological characteristics meeting the medical standard can be taken as the preset state, for example, the heart rate is 60 times/min-100 times/min. The embodiments of the present disclosure are not particularly limited thereto.

Step S730, determining a third biometric feature based on the duration.

After performing a specific action, the user in different physical states may have different durations for the exercise biometric to return to the preset state, e.g., a longer duration may be required for a person with a potential health threat.

In some possible embodiments, the length of time required for the exercise biometric to return to the preset state may be directly used as the third biometric to characterize the biometric recovery capability of the target user after exercise.

In some possible embodiments, to further increase the accuracy of the third biometric feature, another way of determining the third biometric feature is provided.

As shown in FIG. 8, firstly, a target user obtains a time period through statistics after the target action is executed, secondly, a corresponding correction weight is determined according to the action type of the target action, the correction weight is determined in advance according to the biological feature restoration capability of a healthy user after the actions of different action types are executed, and finally, a third biological feature is determined by combining the correction weight and the time period.

The time length required for the same user after rope skipping and sit-up may be different, or even a large difference. By setting the correction weights, the purpose 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, and the influence of the action type made by the target user is eliminated.

The following describes a procedure for determining correction weights corresponding to respective action types in advance based on the biometric recovery capability of a healthy user after the execution of actions of different action types.

Firstly, counting the biological capacity recovery time of the healthy user after the action type is executed according to each action type, secondly, comparing the biological capacity recovery time of the healthy user corresponding to different action types, and distributing corresponding correction weights to the action types according to the comparison result, wherein the correction weights enable the biological capacity recovery time corresponding to the action types to be the same.

For example, for action type 1, action type 2, &..the action type N, the bioengineering time corresponding to the healthy user is a seconds, b seconds, respectively, & ltth & gt, N seconds, after the correction weights x1, x2, respectively are assigned, respectively, & ltc & gt, xn, such that a×x1=b×x2. & ltc & gt, n×xn.

Furthermore, in actual implementation, the third biological feature is determined by combining the correction weight corresponding to the target action and the time required for the target action to recover to the preset state, so that the influence of the action type on the time can be eliminated, the third biological feature is truly and completely dependent on the physical state of the target user, and the accuracy of determining the third biological feature is improved.

It should be noted that, the above assignment weights are given by a×x1=b×x2, and =n×xn is merely exemplary, and the embodiment of the present disclosure may determine the assignment weights in other ways so that the biological ability recovery times corresponding to the respective action types are the same, which is not particularly limited.

In an exemplary embodiment, if the number of the motion biological features of the target user after the target motion is performed is multiple, a duration corresponding to each motion biological feature is obtained, and further, a third biological feature may be determined by combining the durations corresponding to the motion biological features.

The average value of the corresponding duration of each motion biological feature may be obtained as the third biological feature, or a weighted average value of the corresponding duration of each motion biological feature may be obtained according to a preset weight, or a sum value of the corresponding duration of each motion biological feature may be used as the third biological feature, or the like.

For example, if the exercise biometric features include a respiratory rate 2 and a heart rate 2, and the duration corresponding to the respiratory rate 1 and the heart rate 1 restored to the preset state is t1 and t2, respectively, (t1+t2)/2 may be used as the third biometric feature.

According to the method and the device for determining the third biological characteristics, the third biological characteristics are determined by combining the time length required by the target user to restore the plurality of motion biological characteristics after the target user performs the target action to the corresponding preset state, the feature dimension for determining the third biological characteristics is increased, the physical state restoration condition of the target user after the target user performs the target action is reflected more comprehensively, and the accuracy of the third biological characteristics is improved.

In an exemplary embodiment, an implementation of determining an action type of a target action is provided. Before determining the third biometric characteristic based on the length of time, it is also possible to:

presenting candidate actions in response to the test trigger operation;

And responding to the action selection operation, determining an action corresponding to the action selection operation as a target action, and determining the action type of the target action.

Referring to fig. 9, an interactive interface diagram according to an exemplary embodiment of the present disclosure is shown, and a target user may trigger a test of a third biometric feature through the interactive interface diagram shown in fig. 9, and thus perform the test of the third biometric feature with the target user conscious.

With continued reference to fig. 9, the candidate action may also be presented for the target user to select after the target user triggers the test trigger operation. The candidate actions are preset actions, such as sit-ups, rope skipping, running and the like, the target user can select the target actions according to the physical state or individuation requirements of the target user, namely, the action selection operation is executed, the action corresponding to the action selection operation is determined to be the target action, and the action type corresponding to the target action is obtained correspondingly.

In addition, the candidate actions of different action types may also correspond to the same execution time, for example, the execution time corresponding to each candidate action is set to be 1 minute, and after the target user selects the target action, the target user starts to continuously execute the target action for 1 minute. Correspondingly, the biological characteristics collected after 1 minute are the exercise biological characteristics.

Exemplary, a schematic diagram of acquiring athletic biometric is shown in fig. 10, according to an exemplary embodiment of the present disclosure. After the target user selects the target action as running, the target action starts to execute the running action, the target user starts running, the respiratory rate and the heart rate of the target user are acquired after the execution time is 1 minute, further, the time length required for recovering the exercise biological feature to a preset state is started to be m seconds and n seconds respectively, and finally, the third biological feature is determined by combining the m seconds and the n seconds.

By setting the execution time of the target action, the aim is to unify the execution time of different actions of different users to be consistent, and avoid the influence of the execution time difference on the accuracy of the third biological feature.

In another exemplary embodiment, another way of determining the action type of the target action is also provided. The action type of the target action may also be determined from the wireless signal information before the third biometric characteristic is determined based on the length of time.

In the present exemplary embodiment, the third biometric feature may be acquired without perception by the target user. Specifically, if it is determined that the target user is performing an action based on the wireless signal, timing may be started and the exercise biometric may be acquired after the execution time is over.

The wireless signal sent by the wireless WIFI router is reflected based on the body direction after passing through the target user by acquiring the reflection of the wireless signal in the surrounding environment. Based on this, motion event recognition, i.e., recognition of the action type of the target action, can be performed on the RF snapshot based on the signal values from each point in space (i.e., the RF snapshot). Of course, the action type of the target action performed by the target user may be determined based on the wireless signal information in other manners, and the embodiment of the present disclosure does not limit the specific determination manner.

According to the embodiment of the disclosure, the target user does not need to actively trigger the test, and the third biological feature is acquired under the condition that the target user does not feel. Generally, for various reasons, a target user easily ignores health problems and does not actively perform inspection or testing without obvious discomfort, and the embodiments of the present disclosure achieve user-agnostic acquisition of a third biometric by autonomously identifying the target user to perform a target action, and based thereon, acquiring a motion biometric and a type of action thereof.

Furthermore, the second biological characteristic and the sleep quality evaluation result can be obtained under the condition that the target user does not feel, and the whole process of determining the health monitoring information by combining the third biological characteristic, the second biological characteristic and the sleep quality evaluation result can be completely executed under the condition that the target user does not actively trigger or feel, and the health state of the target user is monitored in near real time by timely processing the health data of the target user, so that the early monitoring and intervention on the health problem are facilitated.

In an exemplary embodiment, another method of determining a third biometric feature is also provided. Determining the third biometric characteristic based on the length of time may include:

Obtaining a distance value between the time length and a standard time length, wherein the standard time length is determined in advance according to the biological characteristic recovery time length of the healthy user after the target action is executed, and determining a third biological characteristic based on the distance value.

According to the embodiment of the disclosure, the distance value between the time length corresponding to the target user and the standard time difference is used as the third biological feature, so that the third biological feature reflects the difference between the biological feature recovery capacities of the target user and the healthy human body, namely, the time lengths corresponding to different users are acquired by taking the biological feature recovery capacities of the healthy human body as the reference, and the accuracy of the third biological feature can be further improved.

In an exemplary embodiment, a method of determining health monitoring information is provided. The determining of the health monitoring information in combination with the second biological feature, the third biological feature and the sleep quality assessment result may be:

and importing the second biological characteristic, the third biological characteristic and the sleep quality evaluation result into a health state evaluation model to obtain health monitoring information, wherein the second biological characteristic at least comprises the respiratory frequency and the heartbeat frequency of the target user in an unseen state.

In some possible embodiments, before determining the health monitoring information in combination with the second biometric feature, the third biometric feature, and the sleep quality assessment result, a model may also be trained using training sample data to obtain a health status assessment model.

The method comprises the steps of taking a sleep quality evaluation result sample of a sample user, the respiratory rate and the heart rate of the user when the user does not sleep and the third biological feature as training sample data, and inputting the training sample data into a model to be trained for training. The model to be trained can be any model meeting the requirements, such as a classification model, and the like, and is not particularly limited.

It should be noted that the second biological feature may also include other related biological features in the non-sleep state, such as blood pressure, blood sample saturation, etc., and the embodiments of the present disclosure include, but are not limited to, the second biological feature described above.

In an exemplary embodiment, after the health monitoring information of the target user is obtained, health monitoring is performed on the target user using the health monitoring information as a monitoring index.

The health prompt information can be provided for the terminal of the associated user of the target user in response to the health monitoring information meeting the preset early warning condition.

The preset early warning condition may be that the value of the health monitoring information is greater than a preset threshold, or the preset early warning condition may be that the number of times the data of the health monitoring information is greater than the preset threshold exceeds a preset number of times, or the value of the health monitoring information is located at a preset early warning level (a plurality of early warning levels may be preset, such as a high level, a middle level and a low level), etc., and the embodiments of the disclosure include, but are not limited to, the preset early warning condition described above.

The terminal associated with the target user may be a terminal held by the target user, or may be a terminal device having an association relationship with the terminal held by the target user, for example, a terminal of a guardian of the target user, such as a terminal of a parent, a friend, or a caretaker.

Referring to fig. 11, an interface diagram providing health cue information according to an exemplary embodiment of the present disclosure is shown. When the health monitoring information of the target user meets the preset early warning condition, health prompt information 'you may be in sub-health, please pay attention to relaxation' can be provided to the terminal associated with the target user.

And the association related to the health prompt information, such as an information item and a health analysis item, can be presented on the interactive interface, and further, the corresponding information content can be presented in response to the triggering operation of the target user on the association.

With continued reference to fig. 11, when the target user triggers the information item, sub-health introduction, presentation, prevention, etc. are presented, so that the target user can obtain the health prompt information and simultaneously, can easily confuse the health prompt information.

Referring to fig. 12, another interface diagram providing health cue information according to an exemplary embodiment of the present disclosure is shown. As shown in fig. 12, when the health monitoring information meets the preset early warning condition, health prompt information (including a smart watch and a smart phone) can be provided to the terminal of the target user, and health prompt information can be provided to the terminal of the associated user of the target user.

The health prompt information can also present the association related to the health prompt information, such as sleep quality evaluation result, third biological feature result, health monitoring information and corresponding preset threshold value, so that the user can quickly obtain prompt key content.

The embodiment of the disclosure simultaneously sends the health prompt information to the terminal of the associated user of the target user, and the health state of the target user is known through multiple parties so as to prompt, find and prompt the target user to pay attention to the health problem.

Further, in an exemplary embodiment, another way of providing health cue information is provided. As shown in fig. 13, providing health prompt information to a terminal associated with a target user in response to the health monitoring information satisfying a preset early warning condition may include step S1310 and step S1320:

Step 1310, obtaining the position information of the target user when the health monitoring information meets the preset early warning condition in the preset period.

And the preset period can be a period of historical time taking the current moment as a starting point, if the current time is 2023, 5, month and 12 days, the preset period can be between 2023, 5, month and 1 day and 2023, 5, month and 12 days, and the position information of the target user when the health monitoring information meets the preset early warning condition in the preset period is acquired.

The location information can be obtained through the positioning of the terminal corresponding to the target user.

Step S1320, if the duration of the position information at the target position exceeds the set threshold, providing health prompt information and corresponding risk early warning information to the terminal associated with the target user.

The risk early warning information is early warning information for indicating that the current health state of the target user is in a specific condition, and for example, the risk early warning information can be early warning information with infectious disease risk, early warning information with high health risk and the like. The target location may be a home, company, hospital, or the target location may be a finer division, such as a bathroom, kitchen, etc. in the home of the target user. The embodiment of the disclosure can determine the target position according to actual conditions.

Taking a residence with a target position as a target user as an example, when the position information of the target user is found to be in the residence when the health detection information of the target user meets the preset early warning condition, providing health prompt information and corresponding risk early warning information to a terminal associated with the target user. In this case, the user is in the house for a long time and has health problems, and then risk early warning information can be provided to the associated terminal at the same time so as to warn the related user of special attention.

Taking a bathroom in a residence with a target position as a target user as an example, when the position information of the target user when the health detection information of the target user meets the preset early warning condition is found to be located in the bathroom of the residence, in this case, the target user may have risks of related infectious diseases, such as malaria, abdominal pain, nausea, diarrhea and the like, and the risk early warning information with the risk of infection can be provided at the same time when the health prompt information is sent, so that the related user reduces unnecessary contact and the transmission rate of infectious diseases.

It should be noted that, by way of example, the above examples are given, and in the embodiment of the present disclosure, when the duration of the location information of the target user at the target location exceeds the predetermined threshold, risk early warning information is increased, health attention to the target user is improved, intervention and treatment are timely performed, and infection risk is reduced.

Fig. 14 shows a complete flow chart of a health monitoring method according to an exemplary embodiment of the present disclosure, which is described below in connection with fig. 14.

First, acquiring a first biological feature and a second biological feature according to wireless signal information of a scene where a target user is located.

The first biological characteristic corresponds to a sleep state, and the second sleep characteristic corresponds to an unseen state, such as heart rate and respiratory rate in the unseen state. The first biometric characteristic includes at least a sleep duration, a deep sleep duration, and a respiratory rate during sleep, among others.

Secondly, determining a sleep quality evaluation result of the target user based on the first biological characteristics.

And evaluating the first biological characteristic by using a pre-trained sleep quality evaluation model to obtain a sleep quality evaluation result.

And then, acquiring a third biological characteristic of the target user after the target user performs the target action, wherein the third biological characteristic is used for reflecting the biological characteristic recovery capability of the target user after the target user performs the target action.

The target user can know the active triggering test to acquire the third biological feature, or acquire the third biological feature under the condition that the target user does not feel.

Further, health monitoring information is determined in combination with the second biological feature, the third biological feature and the sleep quality evaluation result.

And importing the second biological characteristic, the third biological characteristic and the sleep quality evaluation result into a pre-trained health state evaluation model to obtain health monitoring information.

Details of the above steps are described in the above method embodiments, and are not described herein.

Further, whether the health monitoring information meets the preset early warning condition is judged.

If the health monitoring information is greater than the preset threshold, health prompt information can be provided for the terminal associated with the target user.

And finally, acquiring whether the times of the health monitoring information meeting the preset early warning conditions meet the preset times or not.

If the health monitoring information meets the number of times of the preset early warning condition, providing health prompt information to a terminal associated with the target user, and otherwise, continuing to monitor the physical state of the target user.

It should be noted that in the above steps, the executing body may be a terminal corresponding to the target user, and the executing body may also be a server (e.g. cloud), as shown in fig. 15, for example and not by way of limitation, the wearable device 1510 worn by the target user (e.g. the elderly) collects wireless signal information, and sends the wireless signal information to the server 1520, so that the server 1520 executes the health monitoring information determining method according to the embodiment of the disclosure based on the wireless signal information to obtain the health monitoring information. The server 1520 may continue to determine whether to trigger an early warning based on the health monitoring information, or the server 1520 may feed the health monitoring information back to the wearable device 1510 to cause the wearable device 1510 to determine whether to trigger an early warning by itself.

After the need to trigger the early warning, health cues may be provided to terminals associated with the target user (e.g., wearable device 1510 and terminal device 1530) simultaneously.

In the process, the data processing part occupying the resources can be executed by the server, so that the calculation speed is high, the data processing amount of the user side is reduced, and the energy consumption and the storage are reduced.

In summary, according to the method for determining health monitoring information provided by the embodiment of the disclosure, on one hand, the sleep quality evaluation result of the target user is determined based on the first biological feature, so that the sleep quality of the target user is monitored without perception, and the sleep quality is taken as one of factors affecting the health monitoring information. On the other hand, the third biological characteristic of the target user after the target action is executed is obtained, the non-perception monitoring of the vital sign restoration capability of the target user after the action is executed is realized, the vital sign restoration capability (the third biological characteristic) is taken as one of factors influencing the health monitoring information to increase the determination dimension of the health monitoring information and improve the accuracy of the health monitoring information in consideration of different levels of the vital sign restoration capability of the user with potential health problems and the health user after the action is executed, on the other hand, the second biological characteristic, the third biological characteristic and the sleep quality evaluation result are combined to determine the health monitoring information, and the process combines the static health data (sleep state) and the dynamic health data (after the target action is executed) of the target user. In addition, emotional tension of the target user in the health examination to the special detection part is avoided, and the accuracy of health monitoring is further improved.

It is noted that the above-described figures are merely schematic illustrations of processes involved in a method according to exemplary embodiments of the present disclosure, and are not intended to be limiting. It will be readily appreciated that the processes shown in the above figures do not indicate or limit the temporal order of these processes. In addition, it is also readily understood that these processes may be performed synchronously or asynchronously, for example, among a plurality of modules.

Further, referring to fig. 16, in an exemplary embodiment of the present disclosure, a health monitoring information determining apparatus 1600 is provided, which includes a first feature acquisition module 1610, a first processing module 1620, a second feature acquisition module 1630, and a second processing module 1640. Wherein:

The system comprises a first feature acquisition module 1610, a first processing module 1620, a second feature acquisition module 1630 and a second processing module 1640, wherein the first feature acquisition module 1610 is used for acquiring biological features according to wireless signal information of a scene where a target user is located, the biological features comprise a first biological feature corresponding to a sleep state and a second biological feature corresponding to a non-sleep state, the first processing module 1620 is used for determining a sleep quality evaluation result of the target user based on the first biological feature, the second feature acquisition module 1630 is used for acquiring a third biological feature of the target user after the target user performs a target action, the third biological feature is used for reflecting biological feature recovery capability of the target user after the target user performs the target action, and the second processing module 1640 is used for determining health monitoring information by combining the second biological feature, the third biological feature and the sleep quality evaluation result.

In an exemplary embodiment, the wireless signal information includes a WIFI signal, and the first feature acquisition module 1610 is configured to acquire channel state information corresponding to the target user in the WIFI environment according to the WIFI signal, and determine the biometric feature based on the channel state information.

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

In an exemplary embodiment, the first processing module 1620 is configured to perform inputting a first biological feature into the sleep quality assessment model to obtain a sleep quality assessment result, wherein the first biological feature includes at least a sleep duration, a deep sleep duration, and a respiratory rate in a sleep state.

In an exemplary embodiment, the first processing module 1620 is configured to perform inputting the first biological feature into the sleep quality assessment model to obtain a model output result, obtaining a historical sleep quality assessment result of the target user, and determining a sleep quality assessment result according to the historical sleep quality assessment result and the model output result.

In an exemplary embodiment, the first processing module 1620 is further configured to determine a sleep quality evaluation model from the candidate sleep evaluation models according to an age level to which the target user belongs, where the candidate sleep evaluation models are trained based on sleep sample data corresponding to the age level.

In an exemplary embodiment, the second feature acquisition module 1630 is configured to perform, based on the wireless signal information, acquiring a motion biometric of the target user after the target action is performed, acquiring a time period required for the motion biometric to return to a preset state, and determining a third biometric based on the time period.

In an exemplary embodiment, the second feature acquisition module 1630 is configured to perform acquiring a correction weight corresponding to the target action, where the correction weight is determined in advance according to a biological feature recovery capability of the healthy user after performing actions of different action types, and determining a third biological feature according to the correction weight and the duration.

In an exemplary embodiment, the health monitoring information determining apparatus 1600 further includes a first determining module configured to perform, in response to the test trigger operation, presenting a candidate action, in response to the action selection operation, determining an action corresponding to the action selection operation as a target action, and determining an action type of the target action.

In an exemplary embodiment, the health monitoring information determining apparatus 1600 further includes a first determining module configured to perform determining a type of action for the target action based on the wireless signal information.

In an exemplary embodiment, the second feature acquisition module 1630 is configured to perform acquiring a distance value between a length of time and a standard length of time, the standard length of time being determined in advance from a biometric recovery length of the healthy user after performing the target action, and determining a third biometric feature based on the distance value.

In an exemplary embodiment, the number of the motion biological features of the target user after the target action is performed is multiple, the second feature obtaining module 1630 is configured to obtain the duration corresponding to each motion biological feature, and determine a third biological feature in combination with the duration corresponding to each motion biological feature.

In an exemplary embodiment, the second processing module 1640 is configured to perform importing the second biometric, the third biometric, and the sleep quality assessment result into a health status assessment model to obtain health monitoring information, wherein the second biometric includes at least a respiratory rate and a heartbeat rate of the target user when the target user is in an unmeshed state.

In an exemplary embodiment, the health monitoring information determining apparatus 1600 further includes a response module configured to perform providing health cue information to a terminal associated with the target user in response to the health monitoring information meeting a preset pre-alarm condition.

In an exemplary embodiment, the response module is further configured to obtain location information of the target user in a predetermined period when the health monitoring information meets a preset early warning condition, and provide health prompt information and corresponding risk early warning information to a terminal associated with the target user if a duration of the location information in the target location exceeds a set threshold.

The specific details of each module in the above apparatus are already described in the method section, and the details that are not disclosed can be referred to the embodiment of the method section, so that they will not be described in detail.

Those skilled in the art will appreciate that the various aspects of the present disclosure may be implemented as a system, method, or program product. Accordingly, aspects of the present disclosure may be embodied in the form of an entirely hardware embodiment, an entirely software embodiment (including firmware, micro-code, etc.) or an embodiment combining hardware and software aspects that may be referred to herein collectively as a "circuit," module, "or" system.

The exemplary embodiment of the disclosure also provides an electronic device for the method, and the electronic device may be the imaging device or the server. Generally, the electronic device comprises at least a processor and a memory for storing executable instructions of the processor, the processor being configured to perform the above-described method via execution of the executable instructions.

The configuration of the electronic device in the embodiment of the present disclosure is exemplarily described below taking the mobile terminal 1700 in fig. 17 as an example. It will be appreciated by those skilled in the art that the configuration of fig. 17 can be applied to stationary type devices in addition to components specifically for mobile purposes. In other embodiments, mobile terminal 1700 may include more or less components than illustrated, or may combine certain components, or split certain components, or a different arrangement of components. The illustrated components may be implemented in hardware, software, or a combination of software and hardware. The interfacing relationship between the components is shown schematically and does not constitute a structural limitation of the mobile terminal 1700. In other embodiments, the mobile terminal may also employ a different interface from that of fig. 17, or a combination of multiple interfaces.

Referring to fig. 17, the mobile terminal 1700 includes Radio Frequency (RF) circuitry 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.

The RF circuit 1710 can be used for receiving and transmitting signals during the process of receiving and transmitting information or communication, in particular, receiving downlink information from a base station, processing the downlink information by the processor 1780, and transmitting uplink data to the base station. Typically, RF circuitry includes, but is not limited to, antennas, at least one amplifier, transceivers, couplers, low noise amplifiers (Low Noise Amplifier, LNAs), diplexers, and the like. In addition, the RF circuitry 1710 may also communicate with networks and other devices through wireless communications. The wireless communication may use any communication standard or protocol including, but not limited to, global system for mobile communications (Global System of Mobile communication, GSM), 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 message Service (Short MESSAGING SERVICE, SMS), and the like.

The memory 1720 may be used to store software programs and modules, and the processor 1780 may perform various functional applications and data processing of the mobile terminal by executing the software programs and modules stored in the memory 1720, such as storing received information in the memory 1720. The memory 1720 may mainly include a storage program area which may store an operating system, an application program required for at least one function (such as a sound playing function, an image playing function, etc.), etc., and a storage data area which may store data created according to the use of the mobile terminal (such as audio data, phonebook, etc.), etc., and may also store data fed back by other terminals. Further, memory 1720 may include high-speed random access memory, and may also include non-volatile memory, such as at least one magnetic disk storage device, flash memory device, or other volatile solid-state storage device.

The input unit 1730 may be used to receive input numerical or character information and generate key signal inputs related to user settings and function controls of the terminal 1700. In particular, the input unit 1730 may include a touch panel 1731 and other input devices 1732. Touch panel 1731, also referred to as a touch screen, may collect touch operations thereon or thereabout by a user (e.g., operations of the user on touch panel 1731 or thereabout using any suitable object or accessory such as a finger, stylus, etc.) and actuate the corresponding connection device according to a predetermined program.

The display unit 1740 may be used to display information input by a user or provided to the user and various menus of the mobile terminal, such as output of the received health cue information. The display unit 1740 may include a display panel 1741, and 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 (OLED), or the like. Further, the touch panel 1731 may overlay the display panel 1741, and when the touch panel 1731 detects a touch operation thereon or thereabout, the touch panel is transferred to the processor 1780 to determine the type of touch event, and then the processor 1780 provides a corresponding visual output on the display panel 1741 according to the type of touch event. Although in fig. 17, the touch panel 1731 and the display panel 1741 are two separate components to implement the input and output functions of the mobile terminal, in some embodiments, the touch panel 1731 may be integrated with the display panel 1741 to implement the input and output functions of the mobile terminal.

The mobile terminal 1700 may also include at least one sensor 1750, such as a light sensor, a motion sensor, and other sensors. In particular, the light sensor may include an ambient light sensor that may adjust the brightness of the display panel 1741 according to the brightness of ambient light and a proximity sensor that may turn off the display panel 1741 and/or the backlight when the mobile terminal is moved to the ear. The accelerometer sensor can detect the acceleration in all directions (generally three axes), can detect the gravity and the direction when the accelerometer sensor is static, can be used for identifying the gesture of the mobile terminal (such as transverse and vertical screen switching, related games, magnetometer gesture calibration), vibration identification related functions (such as pedometer and knocking), and the like, and other sensors such as gyroscopes, barometers, hygrometers, thermometers, infrared sensors and the like which are also configured by the mobile terminal are not repeated herein.

Audio circuitry 1760, speaker 1761, microphone 1762 may provide an audio interface between a user and the mobile terminal. The audio circuit 1760 may convert the received audio data into an electrical signal, transmit the electrical signal to the speaker 1761, and convert the electrical signal to a sound signal for output by the speaker 1761, while the microphone 1762 converts the collected sound signal into an electrical signal, receives the electrical signal from the audio circuit 1760, converts the electrical signal into audio data, processes the audio data with the audio data output processor 1780, sends the audio data to another mobile terminal, for example, via the RF circuit 110, or outputs the audio data to the memory 1720 for further processing. For example, the mobile terminal may play the health prompt information through the audio circuit 1760 and notify the user by means of a voice signal.

The near field communication module 1770 is integrated with a bluetooth communication module, establishes communication connection with the wearable device through the bluetooth communication module, and receives health prompt information or biological characteristics fed back by the wearable device. Although fig. 17 shows a near field communication module 1770, it is understood that it does not belong to the essential constitution of the mobile terminal 1700, and can be omitted entirely within a range not changing the essence of the application as required.

The processor 1780 is a control center of the mobile terminal, connects various parts of the entire mobile terminal using various interfaces and lines, and performs various functions of the mobile terminal and processes data by running or executing software programs and/or modules stored in the memory 1720, and invoking data stored in the memory 1720, thereby performing overall monitoring of the mobile terminal. In the alternative, the processor 1780 may include one or more processing units, and preferably the processor 1780 may integrate an application processor and a modem processor, wherein the application processor primarily processes operating systems, user interfaces, application programs, etc., and the modem processor primarily processes wireless communications. It will be appreciated that the modem processor described above may not be integrated into the processor 1780.

The mobile terminal 1700 also includes a power source 1790 (e.g., a battery) for powering the various components, which can be logically coupled to the processor 1780 by a power management system, such as to perform functions for managing charging, discharging, and power consumption by the power management system.

Furthermore, exemplary embodiments of the present disclosure also provide a computer-readable storage medium having stored thereon a program product capable of implementing the above-described method of the present specification. In some possible implementations, various aspects of the disclosure may also be implemented in the form of a program product comprising program code for causing a terminal device to carry out the steps according to the various exemplary embodiments of the disclosure as described in the "exemplary methods" section of this specification, when the program product is run on the terminal device.

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 two. The computer readable storage medium can be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or a combination of any of the foregoing. More specific examples of a computer-readable storage medium may include, but are not limited to, an electrical connection having one or more wires, a portable computer diskette, 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 disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

In the context of this disclosure, a computer-readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. In the present disclosure, however, the computer-readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, with the computer-readable program code embodied therein. Such a propagated data signal may take any of a variety of forms, including, but not limited to, electro-magnetic, optical, or any suitable combination of the foregoing. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.

Furthermore, the program code for carrying out operations of the present disclosure may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, C++ or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computing device, partly on the user's device, as a stand-alone software package, partly on the user's computing device, partly on a remote computing device, or entirely on the remote computing device or server. In the case of remote computing devices, the remote computing device may be connected to the user computing device through any kind 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., connected via the Internet using an Internet service provider).

Other embodiments of the disclosure will be apparent to those skilled in the art from consideration of the specification and practice of the disclosure disclosed herein. This application is intended to cover any adaptations, uses, or adaptations of the disclosure following, in general, the principles of the disclosure and including such departures from the present disclosure as come within known or customary practice within the art to which the disclosure pertains. It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit of the disclosure being indicated by the following claims.

Claims

1. A method for determining health monitoring information, comprising:

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 is characterized in that the wireless signal information includes a WIFI signal, and the step of acquiring the biometric feature according to the wireless signal information of the scene where the target user is located comprises:

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, wherein 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 determining the sleep quality evaluation result of the target user based on the first biometric feature comprises:

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 comprises:

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 comprises:

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 step of obtaining the third biometric feature of the target user after the target user performs the target action comprises:

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, wherein determining the third biometric feature based on the duration comprises:

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, it also 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, it further comprises:

The action type of the target action is determined according to the wireless signal information.

11. The method according to claim 7, wherein determining the third biometric feature based on the duration comprises:

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 performing the target action, 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, wherein the determining health monitoring information by combining the second biometric feature, the third biometric feature and the sleep quality evaluation result comprises:

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 meeting a preset warning condition, providing health reminder information to a terminal associated with the target user, further comprises:

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, comprising:

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, comprising:

Processor; and

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, wherein when the computer program is executed by a processor, the method according to any one of claims 1 to 15 is implemented.