CN118662111A - Intelligent wearable watch and health monitoring control method thereof - Google Patents
Intelligent wearable watch and health monitoring control method thereof Download PDFInfo
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Abstract
The application provides an intelligent wearable watch and a health monitoring control method thereof, wherein after heart rate monitoring of the intelligent wearable watch is started, an observed heart rate signal of a tested user is obtained, a heart rate fluctuation influence factor of the tested user is determined according to the observed heart rate signal, an interfered heart rate signal interval of the observed heart rate signal is determined according to the heart rate fluctuation influence factor, a heart rate differential signal is obtained by carrying out differential regulation on the observed heart rate signal through a preset heart rate differential coefficient, a heart rate fluctuation calibration gradient is determined by the heart rate differential signal and the observed heart rate signal, observed heart rate values in the interfered heart rate signal interval in the observed heart rate signal are reconstructed according to the heart rate fluctuation calibration gradient, an actual heart rate signal of the tested user is obtained, a heart rate state of the tested user is determined according to the actual heart rate signal, and a monitoring result is sent to a monitoring center, so that the accuracy of health monitoring can be improved.
Description
Technical Field
The application relates to the technical field of intelligent watches, in particular to an intelligent wearable watch and a health monitoring control method thereof.
Background
The watch is continuously evolved and innovated in different historical periods and applications, from a mechanical watch to a smart watch, the development of watch technology provides more choices for people, and promotes continuous progress in watch design and manufacture, and the smart watch is a novel watch which is emerging in recent years, combines the appearance and digital technology of the traditional watch, and can be connected to a smart phone to provide functions of notification, health tracking, navigation and the like.
Health monitoring by smart wearable watches is the use of sensor technology to measure and collect data about physical state that can provide information about health and lifestyle to help people manage health better and make medical diagnoses, which has been a problem in the prior art that the accuracy of health monitoring results is inadequate.
Disclosure of Invention
The application provides an intelligent wearable watch and a health monitoring control method thereof, which can improve the accuracy of health monitoring.
In a first aspect, the present application provides a health monitoring control method for an intelligent wearable watch, including the steps of:
Starting heart rate monitoring of the intelligent wearable watch, and acquiring an observed heart rate signal of a tested user;
Determining a heart rate fluctuation influence factor of a tested user according to the observed heart rate signal, and further determining an interfered heart rate signal interval of the observed heart rate signal according to the heart rate fluctuation influence factor;
Performing differential adjustment on the observed heart rate signal through a preset heart rate differential coefficient to obtain a heart rate differential signal, and further determining a heart rate fluctuation calibration gradient through the heart rate differential signal and the observed heart rate signal;
Reconstructing an observed heart rate value in an interfered heart rate signal interval in the observed heart rate signal according to the heart rate fluctuation calibration gradient to obtain an actual heart rate signal of a measured user;
and determining the heart rate state of the tested user according to the actual heart rate signal, and sending a monitoring result to a monitoring center.
In some embodiments, reconstructing an observed heart rate value in an interfered heart rate signal interval in the observed heart rate signal according to the heart rate fluctuation calibration gradient to obtain an actual heart rate signal of the measured user specifically includes:
determining an actual heart rate value in an interfered heart rate signal interval in the observed heart rate signal according to the heart rate fluctuation calibration gradient and the observed heart rate value;
acquiring an undisturbed observed heart rate value in the observed heart rate signal;
taking the actual heart rate value and an undisturbed observed heart rate value in the observed heart rate signal as actual observed heart rate values;
and determining the actual heart rate signals of the tested user according to all the actual observed heart rate values.
In some embodiments, determining the heart rate fluctuation influence factor of the measured user from the observed heart rate signal specifically includes:
Determining a heart rate sequence from the observed heart rate signal;
Carrying out standardization processing on the heart rate sequence to obtain a reference heart rate sequence;
Determining a time weight value of the observed heart rate signal in a time direction;
determining a heart rate weight value of the observed heart rate signal in the direction of an observed heart rate value according to the heart rate sequence;
determining an intermediate weighting value corresponding to the intermediate moment of the observed heart rate signal;
Determining a neighborhood weighting value corresponding to the neighborhood heart rate moment according to the intermediate moment;
And determining a heart rate fluctuation influence factor according to the reference heart rate sequence, the time weight value of the observed heart rate signal in the time direction, the heart rate weight value of the observed heart rate signal in the direction of the observed heart rate value, the middle time of the observed heart rate signal, the middle weight value corresponding to the middle time, the neighborhood heart rate time and the domain weight value corresponding to the neighborhood heart rate time.
In some embodiments, determining the disturbed heart rate signal interval of the observed heart rate signal in dependence of the heart rate fluctuation influencing factor comprises:
Determining heart rate fluctuation smoothness according to the heart rate fluctuation influence factor;
and determining an interfered heart rate signal interval of the observed heart rate signal according to the heart rate fluctuation smoothness.
In some embodiments, determining the heart rate fluctuation smoothness from the heart rate fluctuation influencing factor specifically comprises:
Acquiring a reference heart rate sequence;
acquiring the heart rate fluctuation influence factor;
and determining heart rate fluctuation smoothness according to the reference heart rate sequence and the heart rate fluctuation influence factor.
In some embodiments, determining the disturbed heart rate signal interval of the observed heart rate signal from the heart rate fluctuation smoothness specifically comprises:
Dividing the observed heart rate signals according to preset heart rate signal segmentation indexes to obtain a plurality of heart rate signal intervals;
and performing interference judgment on each heart rate signal interval according to the heart rate fluctuation smoothness, and further determining an interfered heart rate signal interval of the observed heart rate signal.
In some embodiments, performing differential adjustment on the observed heart rate signal through a preset heart rate differential coefficient to obtain a heart rate differential signal specifically includes:
presetting a heart rate difference coefficient;
Acquiring a heart rate gradient value corresponding to each observed heart rate value in the heart rate sequence;
And carrying out joint adjustment on each heart rate gradient value and the heart rate differential coefficient to obtain a heart rate differential signal.
In a second aspect, the present application provides an intelligent wearable watch, including a health monitoring control unit, the health monitoring control unit including:
The acquisition module is used for acquiring an observed heart rate signal of a tested user after starting heart rate monitoring of the intelligent wearable watch;
The processing module is used for determining a heart rate fluctuation influence factor of a tested user according to the observed heart rate signal, and further determining an interfered heart rate signal interval of the observed heart rate signal according to the heart rate fluctuation influence factor;
The processing module is further used for carrying out differential adjustment on the observed heart rate signal through a preset heart rate differential coefficient to obtain a heart rate differential signal, and further determining a heart rate fluctuation calibration gradient through the heart rate differential signal and the observed heart rate signal;
the processing module is further used for reconstructing observed heart rate values in an interfered heart rate signal interval in the observed heart rate signals according to the heart rate fluctuation calibration gradient to obtain actual heart rate signals of the detected user;
and the monitoring module is used for determining the heart rate state of the tested user according to the actual heart rate signal and sending a monitoring result to the monitoring center.
In a third aspect, the present application provides a computer device, the computer device including a memory for storing a computer program and a processor for calling and running the computer program from the memory, so that the computer device performs the method for controlling health monitoring of the smart wearable watch described above.
In a fourth aspect, the present application provides a computer readable storage medium, where instructions or codes are stored, when the instructions or codes run on a computer, the instructions or codes cause the computer to implement the method for controlling health monitoring of an intelligent wearable watch.
The technical scheme provided by the embodiment of the application has the following beneficial effects:
The application acquires the observed heart rate signal of the measured user after starting the heart rate monitoring of the intelligent wearable watch, determines the heart rate fluctuation influence factor of the measured user according to the observed heart rate signal, the heart rate fluctuation influence factor is a parameter for evaluating the mutation degree of the observed heart rate signal, the larger the heart rate fluctuation influence factor is, the larger the mutation degree of the observed heart rate signal is, the interfered heart rate signal interval of the observed heart rate signal is determined by the heart rate fluctuation influence factor, the specific interval of the observed heart rate signal which needs to be reconstructed is defined, then the observed heart rate signal is subjected to differential regulation according to the preset heart rate differential coefficient to obtain a heart rate differential signal, determining a heart rate fluctuation calibration gradient through the heart rate differential signal and the observed heart rate signal, wherein the heart rate fluctuation calibration gradient is used for representing the change degree and the change direction of the observed heart rate signal at corresponding time in an interfered heart rate signal interval, therefore, lost data, namely the actual observed heart rate value corresponding to the actual heart rate signal of the tested user, can more accurately reflect the real-time heart rate of the tested user, enhances the accuracy and reliability of the real-time heart rate of the tested user, and can enable the accuracy of the final health monitoring result to be higher.
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In order to more clearly illustrate the embodiments of the application or the technical solutions of the prior art, the drawings which are used in the description of the embodiments or the prior art will be briefly described, it being obvious that the drawings in the description below are only some embodiments of the application, and that other drawings can be obtained according to these drawings without inventive faculty for a person skilled in the art.
FIG. 1 is an exemplary flow chart of a method of health monitoring control of a smart wearable watch according to some embodiments of the application;
FIG. 2 is an exemplary flowchart illustrating determining heart rate fluctuation smoothness according to some embodiments of the present application;
FIG. 3 is an exemplary flow chart of determining an actual heart rate signal according to some embodiments of the application;
FIG. 4 is a schematic diagram of exemplary hardware and/or software of a health monitoring control unit shown in accordance with some embodiments of the present application;
Fig. 5 is a schematic structural diagram of a computer device implementing a method for health monitoring control of a smart wearable watch according to some embodiments of the application.
Detailed Description
The following description of the embodiments of the present application will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present application, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to be within the scope of the application.
The embodiment of the application provides an intelligent wearable watch and a health monitoring control method thereof, and the intelligent wearable watch is characterized in that heart rate monitoring is started, an observed heart rate signal of a tested user is obtained, a heart rate fluctuation influence factor of the tested user is determined according to the observed heart rate signal, an interfered heart rate signal interval of the observed heart rate signal is determined according to the heart rate fluctuation influence factor, the observed heart rate signal is subjected to differential regulation according to a preset heart rate differential coefficient to obtain a heart rate differential signal, a heart rate fluctuation calibration gradient is determined according to the heart rate differential signal and the observed heart rate signal, observed heart rate values in the interfered heart rate signal interval in the observed heart rate signal are reconstructed by the heart rate fluctuation calibration gradient, an actual heart rate signal of the tested user is obtained, a heart rate state of the tested user is determined according to the actual heart rate signal, and a monitoring result is sent to a monitoring center, so that the accuracy of health monitoring can be improved.
In order to better understand the above technical solutions, the following detailed description will refer to the accompanying drawings and specific embodiments. Referring to fig. 1, which is an exemplary flowchart of a method of health monitoring control of a smart wearable watch according to some embodiments of the present application, the method 100 of health monitoring control of a smart wearable watch mainly includes the steps of:
In step 101, heart rate monitoring of the smart wearable watch is initiated and an observed heart rate signal of the user under test is obtained.
When the intelligent wearable watch is specifically implemented, after heart rate monitoring of the intelligent wearable watch is started, the built-in optical heart rate sensor in the intelligent wearable watch collects heart rate values of a detected user in real time by irradiating the skin of the detected user and detecting changes of reflected light, and then the collected heart rate values are taken as observed heart rate values, and a data processor in the intelligent wearable watch generates observed heart rate signals of the detected user according to the obtained observed heart rate values and the collection time corresponding to the observed heart rate values.
It should be noted that, in the present application, the heart rate value of the measured user is collected in real time according to the designated frequency, and in some embodiments, the designated frequency may be set according to actual requirements, for example: when the heart rate of the measured user needs to be monitored at a high frequency, the heart rate value of the measured user is collected in real time according to the frequency collected once a second, and when the heart rate of the measured user needs to be monitored at a low frequency, the heart rate value of the measured user is collected in real time according to the frequency collected once five minutes, in other embodiments, the designated frequency can be set by adopting other methods, and the method is not particularly limited herein.
In step 102, a heart rate fluctuation influencing factor of the measured user is determined according to the observed heart rate signal, and then an interfered heart rate signal section of the observed heart rate signal is determined according to the heart rate fluctuation influencing factor.
In some embodiments, determining the heart rate fluctuation influence factor of the tested user according to the observed heart rate signal can be achieved by the following steps:
Determining a heart rate sequence from the observed heart rate signal;
Carrying out standardization processing on the heart rate sequence to obtain a reference heart rate sequence;
Determining a time weight value of the observed heart rate signal in a time direction;
determining a heart rate weight value of the observed heart rate signal in the direction of an observed heart rate value according to the heart rate sequence;
determining an intermediate weighting value corresponding to the intermediate moment of the observed heart rate signal;
Determining a neighborhood weighting value corresponding to the neighborhood heart rate moment according to the intermediate moment;
Determining a heart rate fluctuation influence factor according to the reference heart rate sequence, a time weight value of the observed heart rate signal in the time direction, a heart rate weight value of the observed heart rate signal in the direction of the observed heart rate value, an intermediate time of the observed heart rate signal, an intermediate weight value corresponding to the intermediate time, and a domain weight value corresponding to the neighborhood heart rate time and the neighborhood heart rate time, wherein the heart rate fluctuation influence factor can be determined according to the following formula:
Wherein, Representing the heart rate fluctuation influencing factor,Representing the total number of reference heart rate values in the reference heart rate sequence,Representing the first in a reference heart rate sequenceThe reference heart rate value of each is calculated,Representing the first in a reference heart rate sequenceThe reference heart rate value of each is calculated,Representing the time weight value of the observed heart rate signal in the time direction,Representing the heart rate weight value of the observed heart rate signal in the direction of the observed heart rate value,A constant is represented by a number of times,Representing the standard deviation of the heart rate sequence,Indicating the intermediate timeThe corresponding intermediate weight value is used to determine,Representing neighborhood heart rate timeCorresponding neighborhood weighting values.
In the specific implementation, obtaining an observed heart rate value corresponding to each acquisition time in an observed heart rate signal, and arranging all obtained observed heart rate values according to the sequence of the acquisition times to obtain a heart rate sequence; obtaining the maximum observed heart rate value in the heart rate sequence, selecting a first observed heart rate value in the heart rate sequence, making a difference between the observed heart rate value and the maximum observed heart rate value, further taking the ratio of the difference obtained by making the difference to the standard deviation of the heart rate sequence as the first reference heart rate value in the reference heart rate sequence, selecting a second observed heart rate value in the heart rate sequence, making a difference between the observed heart rate value and the maximum observed heart rate value, further taking the ratio of the difference obtained by making the difference to the standard deviation of the heart rate sequence as the second reference heart rate value in the reference heart rate sequence, and so on, traversing each observed heart rate value in the heart rate sequence to obtain the reference heart rate value corresponding to each observed heart rate value, thereby obtaining the reference heart rate sequence; the derivative of the observed heart rate signal in the time direction can be calculated by using a calculus method to obtain a plurality of time gradient values, normalizing each time gradient value, calculating the average value of all normalized time gradient values to obtain a time gradient average value, carrying out difference between each normalized time gradient value and the time gradient average value to obtain a plurality of difference values, and taking the average value of all the difference values as the time weight value of the observed heart rate signal in the time direction; selecting an observed heart rate value in a heart rate sequence, calculating a difference value between the observed heart rate value and a previous observed heart rate value of the observed heart rate value, taking the difference value as a heart rate gradient value of the observed heart rate value, repeating the steps to obtain heart rate gradient values of the residual observed heart rate values in the heart rate sequence, normalizing each heart rate gradient value, calculating an average value of all normalized heart rate gradient values to obtain a heart rate gradient average value, carrying out difference between each normalized heart rate gradient value and the heart rate gradient average value to obtain a plurality of normalized heart rate gradient difference values, and taking the average value of all normalized heart rate gradient difference values as a heart rate weight value of an observed heart rate signal in the direction of the observed heart rate value; acquiring intermediate moments in time of observed heart rate signalsFurther obtain the intermediate timeThe corresponding observed heart rate value and the normalized heart rate gradient difference value corresponding to the observed heart rate value are used for carrying out the intermediate momentThe product of the corresponding observed heart rate value and the normalized heart rate gradient difference value corresponding to the observed heart rate value is taken as the intermediate momentIntermediate weighting values of (2); Acquiring acquisition time of heart rate signal closest to middle time in time of observation heart rate signal as neighborhood heart rate timeSimilarly, the neighborhood heart rate time is obtainedThe corresponding observed heart rate value and the normalized heart rate gradient difference value corresponding to the observed heart rate value are used for determining the neighborhood heart rate momentThe product of the corresponding observed heart rate value and the normalized heart rate gradient difference value corresponding to the observed heart rate value is taken as the neighborhood heart rate momentNeighborhood weighting value of (2)。
It should be noted that, the heart rate fluctuation influencing factor of the present application is a parameter for evaluating the mutation degree of the observed heart rate signal, and the larger the heart rate fluctuation influencing factor is, the larger the mutation degree of the observed heart rate signal is, and the smaller the heart rate fluctuation influencing factor is, the smaller the mutation degree of the observed heart rate signal is.
In some embodiments, determining the disturbed heart rate signal interval of the observed heart rate signal according to the heart rate fluctuation influencing factor may specifically be implemented by:
Determining heart rate fluctuation smoothness according to the heart rate fluctuation influence factor;
and determining an interfered heart rate signal interval of the observed heart rate signal according to the heart rate fluctuation smoothness.
In some embodiments, reference is made to fig. 2, which is an exemplary flowchart for determining the smoothness of heart rate fluctuations in some embodiments of the present application, where the determination of the smoothness of heart rate fluctuations may be implemented by specifically using the following steps:
first, in step 1021, a reference heart rate sequence is acquired;
Next, in step 1022, the heart rate fluctuation influencing factor is acquired;
Finally, in step 1023, heart rate fluctuation smoothness is determined from the reference heart rate sequence and the heart rate fluctuation influencing factor.
In the above embodiment, in a specific implementation, the heart rate fluctuation smoothness may be determined according to the following formula:
Wherein, Representing the smoothness of the heart rate fluctuations,Representing the heart rate fluctuation influencing factor,Representing the total number of reference heart rate values in the reference heart rate sequence,Representing the first in a reference heart rate sequenceThe reference heart rate value of each is calculated,Representing the first in a reference heart rate sequenceThe reference heart rate value of each is calculated,Representing the first in a reference heart rate sequenceAnd a baseline heart rate value.
The heart rate fluctuation smoothness is an index for measuring the regularity of the fluctuation of the observed heart rate signal, and the higher the heart rate fluctuation smoothness is, the higher the regularity of the fluctuation of the observed heart rate signal is, the lower the heart rate fluctuation smoothness is, and the lower the regularity of the fluctuation of the observed heart rate signal is.
In some embodiments, determining the disturbed heart rate signal interval of the observed heart rate signal according to the heart rate fluctuation smoothness may specifically be implemented by:
Dividing the observed heart rate signals according to preset heart rate signal segmentation indexes to obtain a plurality of heart rate signal intervals;
and performing interference judgment on each heart rate signal interval according to the heart rate fluctuation smoothness, and further determining an interfered heart rate signal interval of the observed heart rate signal.
In specific implementation, the heart rate signal segmentation index can be preset according to the period of the observed heart rate signal, and the duration of the acquisition time of one period corresponding to the observed heart rate signal is used as the heart rate signal segmentation index; dividing the observed heart rate signal according to the heart rate signal segmentation index, for example, assuming that the heart rate signal segmentation index is 0.4s and the total acquisition time of the observed heart rate signal is 60s, the time is then set to beThe corresponding observed heart rate signal in the interval is taken as the first heart rate signal interval, and the time is withinTaking the corresponding observed heart rate signals in the interval as a second heart rate signal interval, and so on until the 60s observed heart rate signals are completely divided, so as to obtain a plurality of heart rate signal intervals; selecting a heart rate signal section, comparing a variance value of an observed heart rate value in the heart rate signal section with heart rate fluctuation smoothness, judging the heart rate signal section as an interfered section when the variance value exceeds the heart rate fluctuation smoothness, repeating the steps, judging the interference of the rest heart rate signal sections, and taking a set of heart rate signal sections corresponding to all the judged interfered sections as the interfered heart rate signal section of the observed heart rate signal.
The method and the device have the advantages that the disturbed heart rate signal section of the observed heart rate signal is determined through the heart rate fluctuation smoothness, the specific section of the observed heart rate signal, which needs to be reconstructed, is defined, and the accuracy and the efficiency of the subsequent reconstruction of the observed heart rate signal are improved.
In step 103, the observed heart rate signal is subjected to differential adjustment through a preset heart rate differential coefficient to obtain a heart rate differential signal, and then a heart rate fluctuation calibration gradient is determined through the heart rate differential signal and the observed heart rate signal.
In some embodiments, the differential adjustment of the observed heart rate signal according to the preset heart rate differential coefficient may specifically be implemented by the following steps:
presetting a heart rate difference coefficient;
Acquiring a heart rate gradient value corresponding to each observed heart rate value in the heart rate sequence;
And carrying out joint adjustment on each heart rate gradient value and the heart rate differential coefficient to obtain a heart rate differential signal.
It should be noted that, the heart rate differential coefficient in the present application is a parameter used to represent the variation and irregularity of the observed heart rate signal, in some embodiments, the heart rate differential coefficient may be preset according to the dispersion and irregularity of the observed heart rate signal, the heart rate differential coefficient generally has a value ranging from 0.1 to 1, and in other embodiments, other methods may be used to preset, which is not limited herein.
In specific implementation, each heart rate gradient value and the heart rate differential coefficient are adjusted in a combined mode to obtain a heart rate differential signal, namely: selecting a heart rate gradient value corresponding to a first observation heart rate value in a heart rate sequence, multiplying the heart rate gradient value by a heart rate differential coefficient, forming a first signal in a heart rate differential signal by the product value and acquisition time corresponding to the first observation heart rate value, selecting a heart rate gradient value corresponding to a second observation heart rate value in the heart rate sequence, multiplying the heart rate gradient value and the heart rate differential coefficient, forming a second signal in the heart rate differential signal by the product value and the acquisition time corresponding to the second observation heart rate value, and so on, traversing the remaining observation heart rate values in the heart rate sequence to obtain a signal corresponding to the remaining observation heart rate value, thereby obtaining the heart rate differential signal.
In some embodiments, determining a heart rate fluctuation calibration gradient from the heart rate differential signal and the observed heart rate signal may be accomplished specifically by:
determining a heart rate fluctuation calibration gradient value according to the heart rate differential signal and the observed heart rate signal;
determining the heart rate fluctuation calibration gradient direction;
The heart rate fluctuation calibration gradient is composed of a heart rate fluctuation calibration gradient value and a heart rate fluctuation calibration gradient direction.
Wherein, in some embodiments, determining a heart rate fluctuation calibration gradient value from the heart rate differential signal and the observed heart rate signal may be accomplished by:
Determining a heart rate proximity correlation coefficient of each adjacent observed heart rate value in the observed heart rate signal, and further determining a maximum heart rate proximity correlation coefficient and standard deviations of all heart rate proximity correlation coefficients;
Acquiring the heart rate differential signal, the heart rate differential coefficient and the heart rate fluctuation smoothness;
Determining a heart rate fluctuation calibration gradient value according to the observed heart rate signal, the maximum heart rate proximity correlation coefficient and standard deviations of all heart rate proximity correlation coefficients, the heart rate differential signal, the heart rate differential coefficient and the heart rate fluctuation smoothness, wherein the heart rate fluctuation calibration gradient value can be determined according to the following formula:
Wherein, Indicating that the observed heart rate signal is at the acquisition timeThe heart rate fluctuation at the time calibrates the gradient value,Indicating the total acquisition time period of the observed heart rate signal,Indicating that the observed heart rate signal is at the acquisition timeThe heart rate value is observed at the time of the process,Representing the differential coefficient of the heart rate,Representing the heart rate differential signal as the acquisition timeThe value of the time-out period,Representing the smoothness of the heart rate fluctuations,Representing the maximum heart rate adjacent to the associated coefficient,Representing the standard deviation of all heart rate neighborhood correlation coefficients.
In the specific implementation, two adjacent observed heart rate values in the observed heart rate signal are taken as adjacent observed heart rate values, and the like, adjacent observed heart rate values of each observed heart rate value in the heart rate signal are determined, the difference value of the observed heart rate values in each adjacent observed heart rate value is determined, the average value of all the difference values is calculated, one adjacent observed heart rate value is selected, the ratio of the difference value of the adjacent observed heart rate value to the average value is taken as the heart rate adjacent correlation coefficient of the adjacent observed heart rate value, and for the rest adjacent observed heart rate values, the steps are repeated to obtain the heart rate adjacent correlation coefficients of the rest adjacent observed heart rate values, and then the maximum heart rate adjacent correlation coefficient and the standard deviation of all the heart rate adjacent correlation coefficients are determined.
Note that, the heart rate proximity correlation coefficient in this embodiment is an index for measuring the correlation strength between adjacent observed heart rate values in the observed heart rate signal, and the larger the heart rate proximity correlation coefficient is, the larger the correlation strength between adjacent observed heart rate values in the observed heart rate signal is, and the smaller the heart rate proximity correlation coefficient is, the smaller the correlation strength between adjacent observed heart rate values in the observed heart rate signal is, and in this embodiment, the heart rate differential signal is at the acquisition time ofValue at timeI.e. in heart rate sequenceAnd multiplying the heart rate gradient value corresponding to the observed heart rate value at the moment by the heart rate difference coefficient to obtain a product value.
In specific implementation, determining the heart rate fluctuation calibration gradient direction may be implemented in the following manner, for example: can be based on the acquisition time in the observed heart rate signal asThe difference between the time difference corresponding to the observed heart rate value and the observed heart rate value at the previous moment and the observed heart rate value is calculated by adopting a trigonometric functionThe included angle between the observed heart rate value and the observed heart rate value at the previous moment is taken as the heart rate fluctuation calibration gradient direction, and in other embodiments, the determination of the heart rate fluctuation calibration gradient direction can be realized in other manners, which is not particularly limited herein.
The heart rate fluctuation calibration gradient in the application is composed of a heart rate fluctuation calibration gradient value and a heart rate fluctuation calibration gradient direction, wherein the heart rate fluctuation calibration gradient is used for representing the change degree and the change direction of the observed heart rate signal at the corresponding time in the interfered heart rate signal interval, and further can be used for recovering the lost observed heart rate value in the interfered heart rate signal interval, the heart rate fluctuation calibration gradient value corresponds to the change degree of the observed heart rate signal at the corresponding time in the interfered heart rate signal interval, and the heart rate fluctuation calibration gradient direction corresponds to the change direction of the observed heart rate signal at the corresponding time in the interfered heart rate signal interval.
In addition, it should be noted that the sensitivity to heart rate variation can be enhanced by determining the heart rate differential signal, and in response to heart rate variation, determining the heart rate fluctuation calibration gradient helps to stabilize and calibrate the heart rate signal, thereby providing more accurate heart rate monitoring.
In step 104, the observed heart rate value in the disturbed heart rate signal interval in the observed heart rate signal is reconstructed according to the heart rate fluctuation calibration gradient, so as to obtain an actual heart rate signal of the tested user.
In some embodiments, reference is made to fig. 3, which is an exemplary flowchart of determining an actual heart rate signal according to some embodiments of the present application, where the determining of the actual heart rate signal may be implemented by:
firstly, in step 1041, determining an actual heart rate value within an interfered heart rate signal interval in the observed heart rate signal according to the heart rate fluctuation calibration gradient and the observed heart rate value;
next, in step 1042, an undisturbed observed heart rate value in the observed heart rate signal is obtained;
then, in step 1043, the actual heart rate value and the undisturbed observed heart rate value in the observed heart rate signal are both taken as actual observed heart rate values;
Finally, in step 1044, the actual heart rate signal of the tested user is determined from all the actual observed heart rate values.
In specific implementation, determining an actual heart rate value in an interfered heart rate signal interval in the observed heart rate signal according to the heart rate fluctuation calibration gradient and the observed heart rate value, namely: the heart rate fluctuation calibration gradient of each acquisition time can be used as the gradient of the corresponding moment in the observed heart rate signal, the actual heart rate value of the corresponding moment in the interfered heart rate signal interval in the observed heart rate signal is determined by a gradient descent method in the prior art, and in other embodiments, the actual heart rate value can be determined by other methods, and the method is not limited herein; in addition, taking the observed heart rate value outside the interfered heart rate signal interval in the observed heart rate signal as an undisturbed observed heart rate value in the observed heart rate signal; determining an actual heart rate signal of the tested user according to all the actual observed heart rate values, namely: and forming the actual heart rate signals of the tested user by all the actual observed heart rate values and the acquisition time corresponding to the actual observed heart rate values.
The heart rate fluctuation calibration gradient is used for obtaining the actual heart rate signal of the measured user, so that the actual heart rate of the measured user can be reflected more accurately, the accuracy and reliability of the actual heart rate of the measured user are enhanced, and the accuracy and reliability of the follow-up intelligent wearable watch for alarming according to the actual heart rate signal of the measured user can be improved.
In step 105, the heart rate state of the user to be tested is determined according to the actual heart rate signal, and the monitoring result is sent to the monitoring center.
When the heart rate of a normal person is preset, an abnormal heart rate threshold value is set to 125 times/minute, the heart rate state of the measured user is determined according to the actual heart rate signals, namely, each actual observed heart rate value in the actual heart rate signals of the measured user is compared with the preset abnormal heart rate threshold value, the heart rate of the measured user is indicated to be excessively fast only when the actual observed heart rate value of the measured user exceeds the abnormal heart rate threshold value and the time when the actual observed heart rate value exceeds the abnormal heart rate threshold value exceeds 5 minutes continuously, the heart rate of the measured user is ensured to be abnormal, the intelligent wearable watch is controlled to send a monitoring result of abnormal heart rate of the measured user to the monitoring center, and the heart rate of the measured user is not processed or the monitoring result of normal heart rate of the measured user is sent to the monitoring center under other conditions.
It should be noted that, according to the actual heart rate signal, the heart rate state of the measured user is determined and the monitoring result is sent to the monitoring center, so that the probability of false alarm of the heart rate abnormality of the measured user by the intelligent wearable watch is reduced, the accuracy of health monitoring of the measured user is enhanced, and the accurate health monitoring of the intelligent wearable watch is realized.
In summary, after the heart rate monitoring of the intelligent wearable watch is started, the observed heart rate signal of the tested user is obtained; the heart rate fluctuation influence factor of the measured user is determined according to the observed heart rate signal, the heart rate fluctuation influence factor is a parameter for evaluating the mutation degree of the observed heart rate signal, the larger the heart rate fluctuation influence factor is, the larger the mutation degree of the observed heart rate signal is, the disturbed heart rate signal interval of the observed heart rate signal is determined according to the heart rate fluctuation influence factor, the specific interval of the observed heart rate signal needing to be reconstructed is defined, then the observed heart rate signal is subjected to differential regulation according to the preset heart rate differential factor to obtain a heart rate differential signal, the heart rate fluctuation calibration gradient is determined through the heart rate differential signal and the observed heart rate signal, and is used for representing the change degree and the change direction of the observed heart rate signal at corresponding time in the disturbed heart rate signal interval.
Additionally, in another aspect of the present application, in some embodiments, the present application provides a smart wearable watch, the system further comprising a health monitoring control unit, referring to fig. 4, which is a schematic diagram of exemplary hardware and/or software of the health monitoring control unit according to some embodiments of the present application, the health monitoring control unit 400 comprising: the acquisition module 401, the processing module 402, and the monitoring module 403 are respectively described as follows:
The acquisition module 401 is mainly used for acquiring an observed heart rate signal of a measured user after starting heart rate monitoring of the intelligent wearable watch;
The processing module 402 is mainly used for determining a heart rate fluctuation influence factor of a tested user according to the observed heart rate signal, and further determining an interfered heart rate signal interval of the observed heart rate signal according to the heart rate fluctuation influence factor;
it should be noted that, in the present application, the processing module 402 is further configured to perform differential adjustment on the observed heart rate signal through a preset heart rate differential coefficient to obtain a heart rate differential signal, so as to determine a heart rate fluctuation calibration gradient according to the heart rate differential signal and the observed heart rate signal;
In addition, the processing module 402 is further configured to reconstruct an observed heart rate value in an interfered heart rate signal interval in the observed heart rate signal according to the heart rate fluctuation calibration gradient, so as to obtain an actual heart rate signal of the measured user;
the monitoring module 403 is mainly configured to determine a heart rate state of the user to be monitored according to the actual heart rate signal, and send a monitoring result to a monitoring center.
While the foregoing details of the example of the smart wearable watch and the health monitoring control method thereof provided by the embodiments of the present application have been described, it may be understood that, in order to implement the foregoing functions, the corresponding device includes a hardware structure and/or a software module that perform each function. Those of skill in the art will readily appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as hardware or combinations of hardware and computer software. Whether a function is implemented as hardware or computer software driven hardware depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.
In some embodiments, the present application further provides a computer device, where the computer device includes a memory and a processor, where the memory is configured to store a computer program, and the processor is configured to call and run the computer program from the memory, so that the computer device performs the method for health monitoring control of the smart wearable watch described above.
In some embodiments, reference is made to fig. 5, in which a dashed line indicates that the unit or the module is optional, which is a schematic structural diagram of a computer device implementing a method for health monitoring control of a smart wearable watch according to an embodiment of the present application. The health monitoring control method of the smart wearable watch in the above embodiment may be implemented by a computer device shown in fig. 5, where the computer device 500 includes at least one processor 501, a memory 502, and at least one communication unit 505, and the computer device 500 may be a terminal device or a server or a chip.
The processor 501 may be a general purpose processor or a special purpose processor. For example, the processor 501 may be a central processing unit (central processing unit, CPU) which may be used to control the computer device 500, execute software programs, process data of the software programs, and the computer device 500 may further comprise a communication unit 505 for enabling input (receiving) and output (transmitting) of signals.
For example, the computer device 500 may be a chip, the communication unit 505 may be an input and/or output circuit of the chip, or the communication unit 505 may be a communication interface of the chip, which may be an integral part of a terminal device or a network device or other devices.
For another example, the computer device 500 may be a terminal device or a server, the communication unit 505 may be a transceiver of the terminal device or the server, or the communication unit 505 may be a transceiver circuit of the terminal device or the server.
The computer device 500 may include one or more memories 502 having a program 504 stored thereon, the program 504 being executable by the processor 501 to generate instructions 503 such that the processor 501 performs the methods described in the method embodiments above in accordance with the instructions 503. Optionally, data (e.g., a goal audit model) may also be stored in memory 502. Alternatively, the processor 501 may also read data stored in the memory 502, which may be stored at the same memory address as the program 504, or which may be stored at a different memory address than the program 504.
The processor 501 and the memory 502 may be provided separately or may be integrated together, for example, on a System On Chip (SOC) of the terminal device.
It should be appreciated that the steps of the above-described method embodiments may be accomplished by logic circuitry in hardware or instructions in software in the processor 501, and the processor 501 may be a CPU, digital signal processor (DIGITAL SIGNAL processor, DSP), application SPECIFIC INTEGRATED Circuit (ASIC), field programmable gate array (field programmable GATE ARRAY, FPGA), or other programmable logic device, such as discrete gates, transistor logic, or discrete hardware components.
It will be appreciated by those skilled in the art that embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
For example, in some embodiments, the present application further provides a computer readable storage medium having instructions or codes stored therein, which when executed on a computer, cause the computer to implement the method for health monitoring control of a smart wearable watch described above.
While preferred embodiments of the present application have been described, additional variations and modifications in those embodiments may occur to those skilled in the art once they learn of the basic inventive concepts. It is therefore intended that the following claims be interpreted as including the preferred embodiments and all such alterations and modifications as fall within the scope of the application.
It will be apparent to those skilled in the art that various modifications and variations can be made to the present application without departing from the spirit or scope of the application. Thus, it is intended that the present application also include such modifications and alterations insofar as they come within the scope of the appended claims or the equivalents thereof.
Claims (10)
1. The health monitoring control method of the intelligent wearable watch is characterized by comprising the following steps of:
Starting heart rate monitoring of the intelligent wearable watch, and acquiring an observed heart rate signal of a tested user;
Determining a heart rate fluctuation influence factor of a tested user according to the observed heart rate signal, and further determining an interfered heart rate signal interval of the observed heart rate signal according to the heart rate fluctuation influence factor;
Performing differential adjustment on the observed heart rate signal through a preset heart rate differential coefficient to obtain a heart rate differential signal, and further determining a heart rate fluctuation calibration gradient through the heart rate differential signal and the observed heart rate signal;
Reconstructing an observed heart rate value in an interfered heart rate signal interval in the observed heart rate signal according to the heart rate fluctuation calibration gradient to obtain an actual heart rate signal of a measured user;
and determining the heart rate state of the tested user according to the actual heart rate signal, and sending a monitoring result to a monitoring center.
2. The method according to claim 1, wherein reconstructing observed heart rate values within an interfered heart rate signal interval in an observed heart rate signal from the heart rate fluctuation calibration gradient, to obtain an actual heart rate signal of the measured user, specifically comprises:
determining an actual heart rate value in an interfered heart rate signal interval in the observed heart rate signal according to the heart rate fluctuation calibration gradient and the observed heart rate value;
acquiring an undisturbed observed heart rate value in the observed heart rate signal;
taking the actual heart rate value and an undisturbed observed heart rate value in the observed heart rate signal as actual observed heart rate values;
and determining the actual heart rate signals of the tested user according to all the actual observed heart rate values.
3. The method according to claim 1, wherein determining a heart rate fluctuation influencing factor of the measured user from the observed heart rate signal comprises:
Determining a heart rate sequence from the observed heart rate signal;
Carrying out standardization processing on the heart rate sequence to obtain a reference heart rate sequence;
Determining a time weight value of the observed heart rate signal in a time direction;
determining a heart rate weight value of the observed heart rate signal in the direction of an observed heart rate value according to the heart rate sequence;
determining an intermediate weighting value corresponding to the intermediate moment of the observed heart rate signal;
Determining a neighborhood weighting value corresponding to the neighborhood heart rate moment according to the intermediate moment;
And determining a heart rate fluctuation influence factor according to the reference heart rate sequence, the time weight value of the observed heart rate signal in the time direction, the heart rate weight value of the observed heart rate signal in the direction of the observed heart rate value, the middle time of the observed heart rate signal, the middle weight value corresponding to the middle time, the neighborhood heart rate time and the domain weight value corresponding to the neighborhood heart rate time.
4. The method according to claim 1, wherein determining the disturbed heart rate signal interval of the observed heart rate signal in dependence of the heart rate fluctuation influencing factor comprises:
Determining heart rate fluctuation smoothness according to the heart rate fluctuation influence factor;
and determining an interfered heart rate signal interval of the observed heart rate signal according to the heart rate fluctuation smoothness.
5. The method of claim 4, wherein determining heart rate fluctuation smoothness from the heart rate fluctuation influencing factor comprises:
Acquiring a reference heart rate sequence;
acquiring the heart rate fluctuation influence factor;
and determining heart rate fluctuation smoothness according to the reference heart rate sequence and the heart rate fluctuation influence factor.
6. The method of claim 4, wherein determining the disturbed heart rate signal interval of the observed heart rate signal from the heart rate fluctuation smoothness comprises:
Dividing the observed heart rate signals according to preset heart rate signal segmentation indexes to obtain a plurality of heart rate signal intervals;
and performing interference judgment on each heart rate signal interval according to the heart rate fluctuation smoothness, and further determining an interfered heart rate signal interval of the observed heart rate signal.
7. The method according to claim 1, wherein the differential adjustment of the observed heart rate signal by a preset heart rate differential coefficient comprises:
presetting a heart rate difference coefficient;
Acquiring a heart rate gradient value corresponding to each observed heart rate value in the heart rate sequence;
And carrying out joint adjustment on each heart rate gradient value and the heart rate differential coefficient to obtain a heart rate differential signal.
8. The utility model provides a wearable wrist-watch of intelligence which characterized in that, including health monitoring control unit, health monitoring control unit includes:
The acquisition module is used for acquiring an observed heart rate signal of a tested user after starting heart rate monitoring of the intelligent wearable watch;
The processing module is used for determining a heart rate fluctuation influence factor of a tested user according to the observed heart rate signal, and further determining an interfered heart rate signal interval of the observed heart rate signal according to the heart rate fluctuation influence factor;
The processing module is further used for carrying out differential adjustment on the observed heart rate signal through a preset heart rate differential coefficient to obtain a heart rate differential signal, and further determining a heart rate fluctuation calibration gradient through the heart rate differential signal and the observed heart rate signal;
the processing module is further used for reconstructing observed heart rate values in an interfered heart rate signal interval in the observed heart rate signals according to the heart rate fluctuation calibration gradient to obtain actual heart rate signals of the detected user;
and the monitoring module is used for determining the heart rate state of the tested user according to the actual heart rate signal and sending a monitoring result to the monitoring center.
9. A computer device, characterized in that the computer device comprises a memory for storing a computer program and a processor for calling and running the computer program from the memory, so that the computer device performs the health monitoring control method of the smart wearable watch according to any one of claims 1 to 7.
10. A computer readable storage medium having instructions or code stored therein which, when run on a computer, cause the computer to perform the method of health monitoring control of a smart wearable watch as claimed in any one of claims 1 to 7.
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