CN113558586A - User health monitoring method and device, terminal equipment and storage medium - Google Patents
User health monitoring method and device, terminal equipment and storage medium Download PDFInfo
- Publication number
- CN113558586A CN113558586A CN202110834130.5A CN202110834130A CN113558586A CN 113558586 A CN113558586 A CN 113558586A CN 202110834130 A CN202110834130 A CN 202110834130A CN 113558586 A CN113558586 A CN 113558586A
- Authority
- CN
- China
- Prior art keywords
- parameter
- physiological
- parameter value
- user
- determining
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000012544 monitoring process Methods 0.000 title claims abstract description 68
- 238000000034 method Methods 0.000 title claims abstract description 55
- 230000036541 health Effects 0.000 title claims abstract description 33
- 230000004962 physiological condition Effects 0.000 claims abstract description 9
- 208000037265 diseases, disorders, signs and symptoms Diseases 0.000 claims description 73
- 230000002159 abnormal effect Effects 0.000 claims description 66
- 201000010099 disease Diseases 0.000 claims description 63
- 238000012545 processing Methods 0.000 claims description 16
- 238000012216 screening Methods 0.000 claims description 16
- 238000013507 mapping Methods 0.000 claims description 14
- 238000004590 computer program Methods 0.000 claims description 12
- 238000012806 monitoring device Methods 0.000 claims description 10
- 230000008569 process Effects 0.000 claims description 6
- 208000024891 symptom Diseases 0.000 claims description 4
- 238000004364 calculation method Methods 0.000 claims description 3
- 230000036760 body temperature Effects 0.000 description 22
- 230000036772 blood pressure Effects 0.000 description 20
- QVGXLLKOCUKJST-UHFFFAOYSA-N atomic oxygen Chemical compound [O] QVGXLLKOCUKJST-UHFFFAOYSA-N 0.000 description 19
- 239000008280 blood Substances 0.000 description 19
- 210000004369 blood Anatomy 0.000 description 19
- 229910052760 oxygen Inorganic materials 0.000 description 19
- 239000001301 oxygen Substances 0.000 description 19
- 238000010586 diagram Methods 0.000 description 7
- 208000035475 disorder Diseases 0.000 description 7
- 230000006870 function Effects 0.000 description 7
- 206010037660 Pyrexia Diseases 0.000 description 4
- 208000026106 cerebrovascular disease Diseases 0.000 description 4
- 238000004891 communication Methods 0.000 description 4
- 238000001514 detection method Methods 0.000 description 4
- 230000003287 optical effect Effects 0.000 description 4
- 206010035664 Pneumonia Diseases 0.000 description 2
- 230000009471 action Effects 0.000 description 2
- 238000004458 analytical method Methods 0.000 description 2
- 230000035487 diastolic blood pressure Effects 0.000 description 2
- 238000005516 engineering process Methods 0.000 description 2
- 206010022000 influenza Diseases 0.000 description 2
- 230000000644 propagated effect Effects 0.000 description 2
- 239000004065 semiconductor Substances 0.000 description 2
- 230000035488 systolic blood pressure Effects 0.000 description 2
- 239000002390 adhesive tape Substances 0.000 description 1
- 230000007812 deficiency Effects 0.000 description 1
- 239000000835 fiber Substances 0.000 description 1
- 230000003862 health status Effects 0.000 description 1
- 239000004973 liquid crystal related substance Substances 0.000 description 1
- 239000000463 material Substances 0.000 description 1
- 239000013307 optical fiber Substances 0.000 description 1
- 239000002699 waste material Substances 0.000 description 1
Images
Classifications
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/02—Detecting, measuring or recording pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography or electroauscultation; Heart catheters for measuring blood pressure
- A61B5/0205—Simultaneously evaluating both cardiovascular conditions and different types of body conditions, e.g. heart and respiratory condition
- A61B5/02055—Simultaneously evaluating both cardiovascular condition and temperature
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/01—Measuring temperature of body parts ; Diagnostic temperature sensing, e.g. for malignant or inflamed tissue
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/74—Details of notification to user or communication with user or patient ; user input means
- A61B5/746—Alarms related to a physiological condition, e.g. details of setting alarm thresholds or avoiding false alarms
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/74—Details of notification to user or communication with user or patient ; user input means
- A61B5/7465—Arrangements for interactive communication between patient and care services, e.g. by using a telephone network
Landscapes
- Health & Medical Sciences (AREA)
- Life Sciences & Earth Sciences (AREA)
- Molecular Biology (AREA)
- Surgery (AREA)
- Biophysics (AREA)
- Pathology (AREA)
- Engineering & Computer Science (AREA)
- Biomedical Technology (AREA)
- Heart & Thoracic Surgery (AREA)
- Medical Informatics (AREA)
- Veterinary Medicine (AREA)
- Physics & Mathematics (AREA)
- Animal Behavior & Ethology (AREA)
- General Health & Medical Sciences (AREA)
- Public Health (AREA)
- Physiology (AREA)
- Cardiology (AREA)
- Nursing (AREA)
- Pulmonology (AREA)
- Measuring And Recording Apparatus For Diagnosis (AREA)
Abstract
The application discloses a method and a device for monitoring user health, terminal equipment and a storage medium, wherein the method comprises the following steps: acquiring physiological information of a user through a contact piece, wherein the physiological information comprises at least one parameter value of a first physiological parameter; analyzing and determining a data grade according to the acquired physiological information, wherein the data grade is used for representing the physiological condition of the user; and displaying the data grade. According to the user health monitoring method and device, the terminal device and the storage medium, the physiological information of the user is collected, the data grade is determined according to the collected physiological information, the data grade is displayed for the user, the user can timely and conveniently know the self health condition through the data grade, and the user experience is improved.
Description
Technical Field
The present invention relates generally to the field of health monitoring technologies, and in particular, to a method and an apparatus for monitoring user health, a terminal device, and a storage medium.
Background
In today's society, more and more people choose to monitor physical information and know their own physical condition. The main parameters to be monitored include body temperature, heart beat, blood pressure, etc.
At present, the mode that people monitored above-mentioned parameter generally monitors for going to the hospital or monitor for self-contained corresponding monitoring facilities (for example clinical thermometer, sphygmomanometer etc.), then with the data feedback of monitoring to the doctor in order to confirm health, can lead to the user to take trouble when acquireing self health status like this and waste efforts, experience is relatively poor.
Disclosure of Invention
In view of the above-mentioned drawbacks and deficiencies of the prior art, it is desirable to provide a method and apparatus for monitoring user health, a terminal device, and a storage medium.
In a first aspect, the present application provides a method for monitoring user health, including:
acquiring physiological information of a user through a contact piece, wherein the physiological information comprises at least one parameter value of a first physiological parameter;
analyzing and determining a data grade according to the acquired physiological information, wherein the data grade is used for representing the physiological condition of the user;
and displaying the data grade.
Further, analyzing and determining the data grade according to the acquired physiological information comprises the following steps:
determining a basic data value of the parameter value of each first physiological parameter;
carrying out weighted summation processing on basic data values of parameter values of all first physiological parameters to obtain sum values;
and determining the data grade according to the sum value and a preset determination rule, wherein the determination rule comprises a mapping relation between the sum value and the data grade.
Furthermore, each first physiological parameter has a plurality of preset first parameter value ranges and basic data values corresponding to the first parameter value ranges one by one, and the first parameter value ranges are different;
determining a base data value for the parameter value of each first physiological parameter, comprising:
judging a first parameter value range to which the parameter value of each first physiological parameter belongs;
and determining the basic data value corresponding to the first parameter value range as the basic data value of the parameter value of the first physiological parameter.
Further, before the weighted summation process, the method further comprises:
acquiring monitoring objects selected by a user, wherein the monitoring objects comprise juveniles and adults;
and determining a corresponding weighting factor group according to a preset matching relationship of the monitoring object selected by the user, wherein the weighting factor group comprises a weighting factor corresponding to each first physiological parameter, and the matching relationship is a single mapping relationship between the monitoring object and the weighting factor group.
Further, each first physiological parameter has a preset first normal parameter value range, and the monitoring method further includes:
judging whether at least part of parameter values of the first physiological parameter are out of the corresponding first normal parameter value range, if so, screening out a target prediction disease from a plurality of preset prediction diseases according to the physiological information, wherein the target prediction disease is used for representing the prediction disease of the user;
displaying the target predicted disorder.
Further, the plurality of predicted symptoms each have a preset at least one second physiological parameter and a parameter quantity threshold, each physiological parameter has a second abnormal parameter value range, and the at least one second physiological parameter is the same as at least part of the first physiological parameter in the physiological information;
screening out a target prediction disease from a plurality of preset prediction diseases according to physiological information, wherein the method comprises the following steps:
respectively acquiring the number of first physiological parameters in the physiological information, which are the same as at least one second physiological parameter in each predicted disease, in a second abnormal parameter value range corresponding to the parameter values;
and judging whether the number reaches the corresponding parameter number threshold value, and if so, determining the predicted disease as the target predicted disease.
Furthermore, each first physiological parameter has a plurality of preset first parameter value ranges, the plurality of first parameter value ranges include a first normal parameter value range and more than two first abnormal parameter value ranges, the more than two first abnormal parameter value ranges correspond to a preset prompt mode of prompt information, and the prompt information is used for prompting the user that the first physiological parameter is abnormal;
the monitoring method further comprises the following steps:
judging a first abnormal parameter value range to which the parameter value of each first physiological parameter belongs, and determining a prompting mode of prompting information according to a judgment result, wherein when at least two of more than two first abnormal parameter value ranges are positioned above or below a first normal parameter value range, the prompting mode corresponding to the first abnormal parameter value range farther from the first normal parameter value range is more prominent;
and displaying prompt information according to the determined prompt mode.
In a second aspect, the present application further provides a device for monitoring user health, comprising:
the system comprises an acquisition unit, a processing unit and a processing unit, wherein the acquisition unit is used for acquiring physiological information of a user, and the physiological information comprises at least one parameter value of a first physiological parameter;
the first determination unit is used for analyzing and determining a data grade according to the acquired physiological information, and the data grade is used for representing the physiological condition of the user;
and the first display unit is used for displaying the data grade.
Further, the first determination unit includes:
the first determination module is used for determining a basic data value of the parameter value of each first physiological parameter;
the first calculation module is used for carrying out weighted summation processing on basic data values of parameter values of all the first physiological parameters to obtain sum values;
and the second determining module is used for determining the data grade according to the sum value and a preset determining rule, and the determining rule comprises a mapping relation between the sum value and the data grade.
Furthermore, each first physiological parameter has a plurality of preset first parameter value ranges and basic data values corresponding to the first parameter value ranges one by one, and the first parameter value ranges are different;
the first determining module includes:
the first judgment submodule is used for judging a first parameter value range to which the parameter value of each first physiological parameter belongs;
and the first determining submodule is used for determining the basic data value corresponding to the first parameter value range as the basic data value of the parameter value of the first physiological parameter.
Further, each first physiological parameter has a preset first normal parameter value range, and the monitoring device further includes:
the first judging unit is used for judging whether at least part of parameter values of the first physiological parameter are positioned outside the corresponding first normal parameter value range;
the screening unit is used for screening out a target prediction disease from a plurality of preset prediction diseases according to the physiological information when at least part of parameter values of the first physiological parameter are out of the corresponding first normal parameter value ranges, and the target prediction disease is used for representing the prediction disease of the user;
a second display unit for displaying the target predicted disorder.
Further, the plurality of predicted symptoms each have a preset at least one second physiological parameter and a parameter quantity threshold, each second physiological parameter has a second abnormal parameter value range, and the at least one second physiological parameter is the same as at least part of the first physiological parameters in the physiological information;
the screening unit includes:
the acquiring module is used for respectively acquiring the number of first physiological parameters in the physiological information, which are the same as at least one second physiological parameter in each predicted disease, in a second abnormal parameter value range corresponding to the parameter values;
the judging module is used for judging whether the number reaches the corresponding parameter number threshold value;
and the third determination module is used for determining the predicted disease as the target predicted disease when the number reaches the corresponding parameter number threshold.
In a third aspect, the present application further provides a terminal device, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor, and when the processor executes the computer program, the monitoring method is implemented.
In a fourth aspect, the present application further provides a computer-readable storage medium having a computer program stored thereon, which when executed by a processor, implements the monitoring method described above.
According to the user health monitoring method and device, the terminal device and the storage medium, the physiological information of the user is collected, the data grade is determined according to the collected physiological information, the data grade is displayed for the user, the user can timely and conveniently know the self health condition through the data grade, and the user experience is improved.
Drawings
Other features, objects and advantages of the present application will become more apparent upon reading of the following detailed description of non-limiting embodiments thereof, made with reference to the accompanying drawings in which:
fig. 1 is a flowchart of a user health monitoring method according to an embodiment of the present application;
FIG. 2 is a flow chart of a method for monitoring user health according to another embodiment of the present application;
FIG. 3 is a flow chart of a method for monitoring user health according to another embodiment of the present application;
FIG. 4 is a flowchart of a method for monitoring health of a user according to yet another embodiment of the present application;
fig. 5 is a block diagram of a monitoring device for user health according to an embodiment of the present disclosure;
fig. 6 is a schematic structural diagram of a terminal device according to an embodiment of the present application.
Detailed Description
The present application will be described in further detail with reference to the following drawings and examples. It is to be understood that the specific embodiments described herein are merely illustrative of the relevant invention and not restrictive of the invention. It should be noted that, for convenience of description, only the portions related to the present invention are shown in the drawings.
It should be noted that the embodiments and features of the embodiments in the present application may be combined with each other without conflict. The present application will be described in detail below with reference to the embodiments with reference to the attached drawings.
Referring to fig. 1, an embodiment of the present application provides a method for monitoring user health, including:
s100: acquiring physiological information of a user through a contact piece, wherein the physiological information comprises at least one parameter value of a first physiological parameter;
s200: analyzing and determining a data grade according to the acquired physiological information, wherein the data grade is used for representing the physiological condition of the user;
s300: and displaying the data grade.
In this embodiment, the monitoring method of the user health is used for monitoring the user health, so as to help the user to know the monitoring condition of the user in time. The monitoring method comprises the following steps: the physiological information of the user is collected through the contact piece, the data grade is determined according to the collected physiological information, the data grade is displayed for the user, the data grade can be determined through the physiological information analysis of the user, the health condition of the user can be timely and conveniently solved through the data grade, the situation that the health condition of the user can be known only by feeding monitoring data back to a doctor is avoided, and the user experience is improved.
The collection mode of the user physiological information may be real-time collection, timing collection, random collection, or the like, which is not limited in this application. Preferably, the acquisition mode of the physiological information of the user is a real-time acquisition mode, so that the health of the user can be monitored in real time, and the user experience is improved.
The physiological information includes one or more parameter values of a first physiological parameter, and the first physiological parameter includes, but is not limited to, body temperature, blood pressure, blood oxygen, heart rate, and the like, which is not limited in this application. The physiological information is acquired through a contact element, and the contact element may be, for example, a mobile terminal or a wearable device having a physiological parameter monitoring function, which is not limited in the present application. For example: the collection piece is an intelligent detection post, the intelligent detection post comprises a shell and a detection device for collecting physiological information of a user, and the detection device is installed on the shell. The housing may be of a flexible material and may be secured to the user's body by adhesive tape or straps.
The data levels may include a first level to an nth level, where n is a positive integer greater than 1. The data levels at each level are uniquely corresponding to different physiological conditions of the user, such as: the first level correspondingly represents that the health condition of the user is good, the second level correspondingly represents that the health condition of the user is good, the third level correspondingly represents that the health condition of the user is general, the fourth level correspondingly represents that the health condition of the user is poor, the fifth level correspondingly represents that the health condition of the user is extremely poor, and the like. Of course, the data rating is not limited to the above-described manner, and the present application does not limit this.
The data grade can be displayed to the user in a terminal screen display mode, which is not limited in the present application.
Referring to fig. 2, in some embodiments of the present application, determining a data rating based on the collected physiological information analysis includes:
s210: determining a basic data value of the parameter value of each first physiological parameter;
s240: carrying out weighted summation processing on basic data values of parameter values of all first physiological parameters to obtain sum values;
s250: and determining the data grade according to the sum value and a preset determination rule, wherein the determination rule comprises a mapping relation between the sum value and the data grade.
In this embodiment, after acquiring the physiological information of the user, the basic data value of each parameter value may be determined according to the parameter value of each first physiological parameter, then the basic data values of all the parameter values of the first physiological parameters are weighted and summed to obtain a sum, and then the data grade is determined according to the sum and a determination rule, so that the data grade can be comprehensively calculated and acquired based on the parameter value of each first physiological parameter, so as to improve the reliability and comprehensiveness of the data grade, and further improve the accuracy of the monitoring method.
The mapping relationship between the sum and the data level may specifically be: each data level is uniquely associated with a different sum range. For example: and if the sum value range is 0-100, the sum value range corresponding to the data grade of the first level is greater than 80 and less than or equal to 100, the sum value range corresponding to the data grade of the second level is greater than 70 and less than or equal to 80, the sum value range corresponding to the data grade of the third level is greater than 60 and less than or equal to 70, the sum value range corresponding to the data grade of the fourth level is greater than 50 and less than or equal to 60, the sum value range corresponding to the data grade of the fifth level is less than or equal to 50, and the like. For another example, if the sum value range is 0 to 10, the sum value range corresponding to the data rank of the first level is greater than 8 and less than or equal to 10, the sum value range corresponding to the data rank of the second level is greater than 7 and less than or equal to 8, the sum value range corresponding to the data rank of the third level is greater than 6 and less than or equal to 7, the sum value range corresponding to the data rank of the fourth level is greater than 5 and less than or equal to 6, the sum value range corresponding to the data rank of the fifth level is less than or equal to 5, and the like. Of course, the mapping relationship between the sum and the data level is not limited to the above, and the application does not limit this.
The weighted summation of the basic data values of the parameter values of all the first physiological parameters is to be understood as: and multiplying the basic data value of the parameter value of each first physiological parameter by a corresponding weighting factor, and then summing the results of the multiplication.
For example: the first physiological parameter in the physiological information comprises the body temperature, the blood pressure, the blood oxygen and the heart rate of a user, the basic data value of the body temperature value is determined according to the body temperature value of the user, the basic data value of the blood pressure value is determined according to the blood pressure value of the user, the basic data value of the blood oxygen value is determined according to the blood oxygen value of the user, the basic data value of the heart rate value is determined according to the heart rate value of the user, and then the basic data values corresponding to the body temperature value, the blood pressure value, the blood oxygen value and the heart rate value are subjected to weighting summation processing to obtain a sum value. Specifically, assuming that the basic data value of the body temperature value is a and the weighting factor is a, assuming that the basic data value of the blood pressure value is B and the weighting factor is B, assuming that the basic data value of the blood oxygen value is C and the weighting factor is C, assuming that the basic data value of the heart rate value is D and the weighting factor is D, the sum is: aa + Bb + Cc + Dd.
In some embodiments of the present application, each first physiological parameter has a plurality of preset first parameter value ranges and basic data values corresponding to the plurality of first parameter value ranges one by one, and the plurality of first parameter value ranges are all different;
determining a base data value for the parameter value of each first physiological parameter, comprising:
s211: judging a first parameter value range to which the parameter value of each first physiological parameter belongs;
s212: and determining the basic data value corresponding to the first parameter value range as the basic data value of the parameter value of the first physiological parameter.
In this embodiment, each first physiological parameter has a plurality of preset first parameter value ranges, and the plurality of first parameter value ranges are different, that is, the plurality of first parameter value ranges are not overlapped. Each first physiological parameter also has a plurality of base data values in one-to-one correspondence with a plurality of first parameter value ranges.
Determining a basic data value of a parameter value of each first physiological parameter specifically includes: the method comprises the steps of judging a first parameter value range to which a parameter value of each first physiological parameter belongs, determining a basic data value of the parameter value of each first physiological parameter according to a judgment result, and calculating and acquiring the basic data value of the parameter value of each first physiological parameter based on the current parameter value range in which the parameter value is located so as to improve the reliability of the data grade and further improve the accuracy of the monitoring method.
For example, when the sum value ranges from 0 to 100 and the physiological information includes the body temperature parameter value, the blood pressure parameter value, the blood oxygen parameter value and the heart rate parameter value, the basic data value of each physiological parameter value can range from 0 to 100. Another example is: when the sum value range is 0-10 and the physiological information comprises a body temperature parameter value, a blood pressure parameter value, a blood oxygen parameter value and a heart rate parameter value, the basic data value of each physiological parameter value can be 0-10. Of course, the basic data value of each first physiological parameter is not limited to the above, and the application does not limit this.
Referring to fig. 3, in some embodiments of the present application, each first physiological parameter has a plurality of preset first parameter value ranges, where the plurality of first parameter value ranges include a first normal parameter value range and two or more first abnormal parameter value ranges, and each of the two or more first abnormal parameter value ranges corresponds to a preset prompting manner of prompting information, where the prompting information is used to prompt a user that the first physiological parameter is abnormal;
the monitoring method further comprises the following steps:
s600: judging a first abnormal parameter value range to which the parameter value of each first physiological parameter belongs, and determining a prompting mode of prompting information according to a judgment result, wherein when at least two of more than two first abnormal parameter value ranges are positioned above or below a first normal parameter value range, the prompting mode corresponding to the first abnormal parameter value range farther from the first normal parameter value range is more prominent;
s700: and displaying prompt information according to the determined prompt mode.
In this embodiment, each first physiological parameter has a plurality of first parameter value ranges, and the plurality of first parameter value ranges include a first normal parameter value range and two or more first abnormal parameter value ranges. The first abnormal parameter value ranges can be both above or below the first normal parameter value range, and can also be above and below the first normal parameter value range. Each first abnormal parameter value range of the first physiological parameter corresponds to a preset prompting mode of prompting information, and the prompting information is used for prompting a user that the first physiological parameter is abnormal. The first normal parameter value range is used for representing the range of the parameter value of the parameter in the normal state, and the first abnormal parameter value range is used for representing the range of the parameter value of the parameter in the abnormal state.
The monitoring method further comprises the following steps: judging a first abnormal parameter value range to which the parameter value of each first physiological parameter belongs, and determining a prompting mode of prompting information according to a judgment result, wherein when at least two of the more than two first abnormal parameter value ranges are positioned above or below the first normal parameter value range, the prompting mode corresponding to the first abnormal parameter value range farther away from the first normal parameter value range is more prominent, and prompting information according to the determined prompting mode, so that the user can be prompted in time when any one first physiological parameter is abnormal, and meanwhile, the prompting information can be prompted according to the corresponding prompting mode in the first abnormal parameter value range where the first physiological parameter is positioned, so that accurate prompting of the user is realized, and the user can be helped to know the abnormal physiological parameters and abnormal degree of the user in time.
The prompt information may be the first physiological parameter and its parameter value, and the prompt mode is, for example, but not limited to, short message prompt, voice prompt, or APP message push, which is not limited in this application.
For example: the first physiological parameter is body temperature, more than two first abnormal parameter value ranges are arranged above or below a first normal parameter value range of the body temperature parameter, and the prompting mode is APP message pushing. When the body temperature value reaches a first abnormal parameter value range close to the first normal parameter value range, the APP pushes orange prompt information; when the body temperature value reaches a first abnormal parameter value range far away from the first normal parameter value range, the APP pushes red prompt information.
In some embodiments of the present application, before the weighted summation process, the method further includes:
s220: acquiring monitoring objects selected by a user, wherein the monitoring objects comprise juveniles and adults;
s230: and determining a corresponding weighting factor group according to a preset matching relationship of the monitoring object selected by the user, wherein the weighting factor group comprises a weighting factor corresponding to each first physiological parameter, and the matching relationship is a single mapping relationship between the monitoring object and the weighting factor group.
In this embodiment, since physiological parameters of different monitored subjects may be different, health scores of different monitored subjects can be more accurately obtained by configuring corresponding weighting factor sets according to the monitored subjects. Specifically, the monitoring object selected by the user is obtained, and then the corresponding weighting factor group is determined according to the preset matching relationship according to the monitoring object selected by the user, wherein the weighting factor group comprises the weighting factor corresponding to each first physiological parameter.
The matching relationship is a single mapping relationship between the monitoring objects and the weighting factor sets, that is, different monitoring objects respectively correspond to the matching weighting factor sets. The number of the weighting factors in the weighting factor group is matched with the number of the first physiological parameters in the physiological information, and the weighting factors in the weighting factor group are arranged in one-to-one correspondence with the first physiological parameters in the physiological information. The weighting factor sets corresponding to different monitored objects have differences, and can be specifically set according to the first physiological parameter. For example: the first physiological parameter of the first physiological information includes body temperature, blood pressure, blood oxygen and heart rate, when the monitored object is a minor, the weighting factor of the body temperature parameter in the weighting factor set may be 0.4, the weighting factor of the blood pressure number of the corresponding body in the weighting factor set may be 0.2, the weighting factor of the blood oxygen parameter in the weighting factor set may be 0.2, and the weighting factor of the heart rate parameter in the weighting factor set may be 0.2. When the monitored subject is an adult, the weighting factor of the corresponding body temperature parameter in the weighting factor set may be 0.2, the weighting factor of the corresponding body blood pressure number in the weighting factor set may be 0.25, the weighting factor of the corresponding blood oxygen parameter in the weighting factor set may be 0.25, and the weighting factor of the corresponding heart rate parameter in the weighting factor set may be 0.3.
Wherein, the non-adult can be divided into children and teenagers, the adult can be divided into adults and the elderly, and the children, the teenagers, the adults and the elderly correspond to different weighting factor groups. Of course, the crowd division (such as working crowd) can be performed according to other rules, which is not limited in the present application.
In some embodiments of the present application, before the weighted summation process, the method further includes:
acquiring an application scene selected by a user;
and determining a corresponding weighting factor group according to the application scene selected by the user and a preset matching relationship, wherein the weighting factor group comprises a weighting factor corresponding to each first physiological parameter, and the matching relationship is a single mapping relationship between the application scene and the weighting factor group.
In the present embodiment, the application scenarios include, but are not limited to, a normal scenario, a new coronary pneumonia scenario, and an influenza scenario. The corresponding weighting factor set is configured according to the application situation, so that the physiological conditions of the user under different operation situations can be more accurately acquired.
The weighting factor sets corresponding to different application scenarios are different and can be specifically set according to the first physiological parameter. For example: the first physiological parameters of the first physiological information include body temperature, blood pressure, blood oxygen and heart rate, when the application scenario is a normal scenario, the weighting factor of the body temperature parameter in the weighting factor set may be 0.25, the weighting factor of the body blood pressure number in the weighting factor set may be 0.25, the weighting factor of the blood oxygen parameter in the weighting factor set may be 0.25, and the weighting factor of the heart rate parameter in the weighting factor set may be 0.25. When the application scenario is new coronary pneumonia, the weighting factor of the body temperature parameter in the weighting factor set may be 0.4, the weighting factor of the body blood pressure number in the weighting factor set may be 0.1, the weighting factor of the blood oxygen parameter in the weighting factor set may be 0.3, and the weighting factor of the heart rate parameter in the weighting factor set may be 0.2. When the application scenario is influenza, the weighting factor of the body temperature parameter in the weighting factor set may be 0.4, the weighting factor of the body blood pressure number in the weighting factor set may be 0.1, the weighting factor of the blood oxygen parameter in the weighting factor set may be 0.25, and the weighting factor of the heart rate parameter in the weighting factor set may be 0.25.
Referring to fig. 4, in some embodiments of the present application, each of the first physiological parameters has a preset first normal parameter value range, and the monitoring method further includes:
s400: judging whether at least part of parameter values of the first physiological parameter are out of the corresponding first normal parameter value range, if so, screening out a target prediction disease from a plurality of preset prediction diseases according to the physiological information, wherein the target prediction disease is used for representing the prediction disease of the user;
s500: displaying the target predicted disorder.
In this embodiment, whether at least part of the parameter values of the first physiological parameter are outside the corresponding first normal parameter value range is judged, if yes, a target predicted disease is screened out from a plurality of preset disease states according to the physiological information, and the target predicted disease is displayed to the user, so that the disease state of the user can be automatically predicted when at least part of the parameter values of the first physiological parameter in the physiological information are abnormal, the user can be helped to preliminarily know the possible disease state of the user, and the user can conveniently and accurately see a doctor in time.
The display mode of the target predicted disease is, for example, but not limited to, a terminal screen display, which is not limited in this application.
In some embodiments of the present application, the plurality of predicted conditions each have a preset threshold value of at least one second physiological parameter and a parameter number, each second physiological parameter having a second abnormal parameter value range, the at least one second physiological parameter being the same as at least a portion of the first physiological parameter in the physiological information;
screening out a target prediction disease from a plurality of preset prediction diseases according to physiological information, wherein the method comprises the following steps:
respectively acquiring the number of first physiological parameters in the physiological information, which are the same as at least one second physiological parameter in each predicted disease, in a second abnormal parameter value range corresponding to the parameter values;
and judging whether the number reaches the corresponding parameter number threshold value, and if so, determining the predicted disease as the target predicted disease.
In this embodiment, each predicted condition is characterized by a corresponding at least one second physiological parameter, and the at least one second physiological parameter is the same as at least a portion of the first physiological parameter in the physiological information. Each second physiological parameter has a second normal parameter value range for characterizing a range of parameter values of the parameter when in a normal state and at least one second abnormal parameter value range for characterizing a range of parameter values of the parameter when in an abnormal state. Each predicted condition has a threshold number of parameters that does not exceed the number of second physiological parameters.
Screening out a target prediction disease from a plurality of preset prediction diseases according to physiological information, and specifically: and respectively acquiring the number of the first physiological parameters in the physiological information, which are the same as at least one second physiological parameter in each predicted disease, in the parameter value range of the corresponding second abnormal parameter value, judging whether the number reaches the corresponding parameter number threshold value, and if so, determining the disease as a matching disease, so that the determination of the matching disease is simple and accurate.
When the physiological information is compared with each predicted disease, first physiological parameters which are the same as second physiological parameters in each predicted disease are obtained, whether the parameter values of the first physiological parameters which are the same as the second physiological parameters in each predicted disease are located in the corresponding second abnormal parameter value ranges is judged, and then the number of the first physiological parameters which are the same as the second physiological parameters in each disease in the second abnormal parameter value ranges is obtained.
Predictive disorders may include, but are not limited to, fever, cerebrovascular disease, and the like. Taking the fever disorder as an example, the fever disorder has a second physiological parameter with a parameter number threshold of 1, the second physiological parameter is body temperature, the second normal parameter value range can be 36.0-37.2 ℃, and the second abnormal parameter value range can be greater than 37.2 ℃ and/or less than 36.0 ℃. And determining that the target prediction disease of the user is fever if the body temperature value in the physiological information is in the second abnormal parameter value range. Taking cerebrovascular disease as an example, cerebrovascular disease has three second physiological parameters, and the threshold value of the number of the parameters is 2 or 3, and the three second physiological parameters are blood pressure, blood oxygen and heart rate respectively. The second normal parameter value range of the blood pressure is that the systolic pressure is 90-140mmHg and the diastolic pressure is 60-90mmHg, and the second abnormal parameter value range is that the systolic pressure is less than 90mmHg or more than 140mmHg and the diastolic pressure is less than 60mmHg or more than 90 mmHg. The second normal parameter value range of blood oxygen is 95-100%, and the second abnormal parameter value range is less than 95%. The second normal parameter value range of the heart rate is 60-100 times/min, and the second abnormal parameter value range is less than 60 times/min or more than 100 times/min. Whether the blood pressure value, the blood oxygen value and the heart rate value in the physiological information are in the second abnormal parameter value range or not is judged respectively, and when at least two of the blood pressure value, the blood oxygen value and the heart rate value are in the corresponding second abnormal parameter value ranges, the target prediction disease of the user can be determined to be cerebrovascular disease.
Referring to fig. 5, an embodiment of the present application further provides a device for monitoring user health, including:
the system comprises an acquisition unit 100, a processing unit and a processing unit, wherein the acquisition unit is used for acquiring physiological information of a user, and the physiological information comprises at least one parameter value of a first physiological parameter;
a first determining unit 200, configured to analyze and determine a data grade according to the acquired physiological information, where the data grade is used to represent a physiological condition of the user;
a first display unit 300 for displaying the data rating.
Further, the first determination unit 200 includes:
the first determination module is used for determining a basic data value of the parameter value of each first physiological parameter;
the first calculation module is used for carrying out weighted summation processing on basic data values of parameter values of all the first physiological parameters to obtain sum values;
and the second determining module is used for determining the data grade according to the sum value and a preset determining rule, and the determining rule comprises a mapping relation between the sum value and the data grade.
Furthermore, each first physiological parameter has a plurality of preset first parameter value ranges and basic data values corresponding to the first parameter value ranges one by one, and the first parameter value ranges are different;
the first determining module includes:
the first judgment submodule is used for judging a first parameter value range to which the parameter value of each first physiological parameter belongs;
and the first determining submodule is used for determining the basic data value corresponding to the first parameter value range as the basic data value of the parameter value of the first physiological parameter.
Further, still include:
the system comprises an acquisition unit, a selection unit and a display unit, wherein the acquisition unit is used for acquiring monitoring objects selected by a user, and the monitoring objects comprise juveniles and adults;
and the second determining unit is used for determining a corresponding weighting factor group according to the monitored object selected by the user and a preset matching relationship, wherein the weighting factor group comprises a weighting factor corresponding to each first physiological parameter, and the matching relationship is a single mapping relationship between the monitored object and the weighting factor group.
Further, each first physiological parameter has a preset first normal parameter value range, and the monitoring device further includes:
the first judging unit is used for judging whether at least part of parameter values of the first physiological parameter are positioned outside the corresponding first normal parameter value range;
the screening unit is used for screening out a target prediction disease from a plurality of preset prediction diseases according to the physiological information when at least part of parameter values of the first physiological parameter are out of the corresponding first normal parameter value ranges, and the target prediction disease is used for representing the prediction disease of the user;
a second display unit for displaying the target predicted disorder.
Further, the plurality of predicted symptoms each have a preset at least one second physiological parameter and a parameter quantity threshold, each physiological parameter has a second abnormal parameter value range, and the at least one second physiological parameter is the same as at least part of the first physiological parameter in the physiological information;
the screening unit includes:
the acquiring module is used for respectively acquiring the number of first physiological parameters in the physiological information, which are the same as at least one second physiological parameter in each predicted disease, in a second abnormal parameter value range corresponding to the parameter values;
the judging module is used for judging whether the number reaches the corresponding parameter number threshold value;
and the third determination module is used for determining the predicted disease as the target predicted disease when the number reaches the corresponding parameter number threshold.
Furthermore, each first physiological parameter has a plurality of preset first parameter value ranges, the plurality of first parameter value ranges include a first normal parameter value range and more than two first abnormal parameter value ranges, the more than two first abnormal parameter value ranges correspond to a preset prompt mode of prompt information, and the prompt information is used for prompting the user that the first physiological parameter is abnormal;
the monitoring device further comprises:
the second judging unit is used for judging a first abnormal parameter value range to which the parameter value of each first physiological parameter belongs;
a third determining unit, configured to determine a prompting manner of the prompting information according to a first abnormal parameter value range to which a parameter value of each first physiological parameter belongs, where, when at least two of the more than two first abnormal parameter value ranges are located above or below the first normal parameter value range, the prompting manner corresponding to the first abnormal parameter value range farther from the first normal parameter value range is more prominent;
and the prompting unit is used for displaying prompting information according to the determined prompting mode.
It should be understood that each unit described in the monitoring apparatus corresponds to each step in the monitoring method described in the above embodiment. Thus, the operations and features described above for the monitoring method are equally applicable to the monitoring device and the units included therein, and are not described in detail here.
Fig. 6 is a schematic structural diagram of a terminal device according to an embodiment of the present invention. As shown in fig. 6, the terminal device 400 includes a Central Processing Unit (CPU)401 that can perform various appropriate actions and processes in accordance with a program stored in a Read Only Memory (ROM)402 or a program loaded from a storage section into a Random Access Memory (RAM) 403. In the RAM403, various programs and data necessary for system operation are also stored. The CPU401, ROM 402, and RAM403 are connected to each other via a bus 403. An input/output (I/O) interface 405 is also connected to bus 403. The terminal device includes, but is not limited to, a mobile phone, a tablet computer, a watch, and the like.
The following components are connected to the I/O interface 405: an input section 406 including a keyboard, a mouse, and the like; an output section 407 including a display device such as a Cathode Ray Tube (CRT), a Liquid Crystal Display (LCD), and the like, and a speaker; a storage section 408 including a hard disk and the like; and a communication section 409 including a network interface card such as a LAN card, a modem, or the like. The communication section 409 performs communication processing via a network such as the internet. Drivers are also connected to the I/O interface 405 as needed. A removable medium 411 such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, or the like is mounted on the drive 410 as necessary, so that a computer program read out therefrom is mounted into the storage section 408 as necessary.
In particular, the processes described above with reference to flowcharts 1-4 may be implemented as computer software programs, according to embodiments of the present invention. For example, embodiments of the present invention include a computer program product comprising a computer program embodied on a computer-readable medium, the computer program containing program code for performing the control method of the various embodiments described above. In such an embodiment, the computer program may be downloaded and installed from a network via the communication section, and/or installed from a removable medium. The above-described functions defined in the system of the present application are executed when the computer program is executed by a Central Processing Unit (CPU) 401.
It should be noted that the computer readable medium shown in the present invention can be a computer readable signal medium or a computer readable storage medium or any combination of the two. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples of the 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 present invention, 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 invention, however, a computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. 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, wire, fiber optic cable, RF, etc., or any suitable combination of the foregoing.
The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present invention. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams or flowchart illustration, and combinations of blocks in the block diagrams or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
The units described in the embodiments of the present invention may be implemented by software, or may be implemented by hardware, and the described units may also be disposed in a processor. Wherein the names of the elements do not in some way constitute a limitation on the elements themselves. The described units or modules may also be provided in a processor, and may be described as: a processor includes a first determination unit 200, a second determination unit, and the like. Where the names of these units or modules do not in some cases constitute a limitation of the units or modules themselves, for example, the first determination unit 200 may also be described as a "unit for analyzing and determining a data grade based on the acquired physiological information".
As another aspect, the present application also provides a computer-readable medium, which may be contained in the terminal device described in the above embodiments; or may exist separately without being assembled into the terminal device. The computer readable medium carries one or more programs which, when executed by the terminal device, cause the terminal device to implement the monitoring method as described in the above embodiments.
For example, the terminal device may implement the monitoring method as shown in fig. 1: s100: acquiring physiological information of a user through a contact element; s200: analyzing and determining the data grade according to the acquired physiological information; s300: and displaying the data grade.
It should be noted that although in the above detailed description several modules or units of the device for action execution are mentioned, such a division is not mandatory. Indeed, the features and functionality of two or more modules or units described above may be embodied in one module or unit, according to embodiments of the present disclosure. Conversely, the features and functions of one module or unit described above may be further divided into embodiments by a plurality of modules or units. Moreover, although the steps of the methods of the present disclosure are depicted in the drawings in a particular order, this does not require or imply that the steps must be performed in this particular order, or that all of the depicted steps must be performed, to achieve desirable results. Additionally or alternatively, certain steps may be omitted, multiple steps combined into one step execution, and/or one step broken down into multiple step executions, etc.
Through the above description of the embodiments, those skilled in the art will readily understand that the exemplary embodiments described herein may be implemented by software, or by software in combination with necessary hardware.
It is to be understood that the terms "first", "second" and "first" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of the present invention, "a plurality" means two or more unless otherwise specified.
The above description is only a preferred embodiment of the application and is illustrative of the principles of the technology employed. It will be appreciated by a person skilled in the art that the scope of the invention as referred to in the present application is not limited to the embodiments with a specific combination of the above-mentioned features, but also covers other embodiments with any combination of the above-mentioned features or their equivalents without departing from the inventive concept. For example, the above features may be replaced with (but not limited to) features having similar functions disclosed in the present application.
Claims (14)
1. A method for monitoring the health of a user, comprising:
acquiring physiological information of a user through a contact element, wherein the physiological information comprises a parameter value of at least one first physiological parameter;
analyzing and determining a data grade according to the acquired physiological information, wherein the data grade is used for representing the physiological condition of the user;
and displaying the data grade.
2. The monitoring method of claim 1, wherein said analyzing the determined data level based on the collected physiological information comprises:
determining a base data value for the parameter value of each of the first physiological parameters;
carrying out weighted summation processing on basic data values of all parameter values of the first physiological parameter to obtain a sum value;
and determining the data grade according to the sum value and a preset determination rule, wherein the determination rule comprises a mapping relation between the sum value and the data grade.
3. The monitoring method according to claim 2, wherein each of the first physiological parameters has a plurality of preset first parameter value ranges and basic data values corresponding to the first parameter value ranges in a one-to-one manner, and the first parameter value ranges are different;
the determining the basic data value of the parameter value of each first physiological parameter comprises:
judging the first parameter value range to which the parameter value of each first physiological parameter belongs;
and determining the basic data value corresponding to the first parameter value range as the basic data value of the parameter value of the first physiological parameter.
4. The monitoring method of claim 2, further comprising, prior to the weighted sum process:
acquiring monitoring objects selected by a user, wherein the monitoring objects comprise minors and adults;
and determining a corresponding weighting factor group according to the monitoring object selected by the user and a preset matching relationship, wherein the weighting factor group comprises a weighting factor corresponding to each first physiological parameter, and the matching relationship is a single mapping relationship between the monitoring object and the weighting factor group.
5. The monitoring method of claim 1, wherein each of the first physiological parameters has a preset first normal parameter value range, the monitoring method further comprising:
judging whether at least part of parameter values of the first physiological parameter are out of the corresponding first normal parameter value range, if so, screening a target prediction disease from a plurality of preset prediction diseases according to the physiological information, wherein the target prediction disease is used for representing the prediction disease of the user;
displaying the target predictive disorder.
6. The monitoring method according to claim 5, wherein the plurality of predicted conditions each have a preset threshold value of at least one second physiological parameter and a parameter number, each of the physiological parameters having a second abnormal parameter value range, the at least one second physiological parameter being the same as the first physiological parameter of at least part of the physiological information;
the screening of the target prediction disease from a plurality of preset prediction diseases according to the physiological information comprises the following steps:
respectively acquiring the number of the first physiological parameters in the physiological information, which are the same as the at least one second physiological parameter in each predicted disease, in the range of the second abnormal parameter values corresponding to the parameter values;
and judging whether the number reaches a corresponding parameter number threshold value, and if so, determining the predicted disease as a target predicted disease.
7. The monitoring method according to any one of claims 1 to 6, wherein each of the first physiological parameters has a plurality of preset first parameter value ranges, the plurality of first parameter value ranges include a first normal parameter value range and two or more first abnormal parameter value ranges, each of the two or more first abnormal parameter value ranges corresponds to a preset prompting mode of prompting information, and the prompting information is used for prompting a user that the first physiological parameter is abnormal;
the monitoring method further comprises the following steps:
judging the first abnormal parameter value range to which the parameter value of each first physiological parameter belongs, and determining the prompting mode of the prompting information according to the judgment result, wherein when at least two of the more than two first abnormal parameter value ranges are positioned above or below the first normal parameter value range, the prompting mode corresponding to the first abnormal parameter value range farther away from the first normal parameter value range is more prominent;
and displaying the prompt information according to the determined prompt mode.
8. A device for monitoring the health of a user, comprising:
the system comprises an acquisition unit, a processing unit and a processing unit, wherein the acquisition unit is used for acquiring physiological information of a user, and the physiological information comprises at least one parameter value of a first physiological parameter;
the first determination unit is used for analyzing and determining a data grade according to the acquired physiological information, wherein the data grade is used for representing the physiological condition of the user;
and the first display unit is used for displaying the data grade.
9. The monitoring device according to claim 8, wherein the first determination unit includes:
the first determination module is used for determining a basic data value of the parameter value of each first physiological parameter;
the first calculation module is used for carrying out weighted summation processing on basic data values of all parameter values of the first physiological parameter so as to obtain a sum value;
and the second determining module is used for determining the data grade according to the sum value and a preset determining rule, wherein the determining rule comprises the mapping relation between the sum value and the data grade.
10. The monitoring device according to claim 9, wherein each of the first physiological parameters has a plurality of preset first parameter value ranges and basic data values corresponding to the first parameter value ranges, and the first parameter value ranges are different;
the first determining module includes:
the first judgment submodule is used for judging the first parameter value range to which the parameter value of each first physiological parameter belongs;
and the first determining submodule is used for determining the basic data value corresponding to the first parameter value range as the basic data value of the parameter value of the first physiological parameter.
11. The monitoring device of claim 10, wherein each of the first physiological parameters has a preset first normal parameter value range, the monitoring device further comprising:
the first judging unit is used for judging whether at least part of parameter values of the first physiological parameters are positioned outside the corresponding first normal parameter value range;
the screening unit is used for screening out a target prediction disease from a plurality of preset prediction diseases according to the physiological information when at least part of parameter values of the first physiological parameter are out of the corresponding first normal parameter value ranges, and the target prediction disease is used for representing the prediction disease of the user;
a second display unit for displaying the target predicted condition.
12. The monitoring device of claim 11, wherein the plurality of predicted conditions each have a preset threshold of at least one second physiological parameter and a quantity of parameters, each of the second physiological parameters having a second abnormal parameter value range, the at least one second physiological parameter being the same as the first physiological parameter of at least a portion of the physiological information;
the screening unit includes:
an obtaining module, configured to respectively obtain the number of the first physiological parameters in the physiological information that are the same as the at least one second physiological parameter in each of the predicted symptoms, in a range of the second abnormal parameter values whose parameter values are in correspondence;
the judging module is used for judging whether the number reaches a corresponding parameter number threshold value;
a third determination module to determine the predicted disorder as a target predicted disorder when the number reaches a corresponding parameter number threshold.
13. A terminal device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the processor implements the monitoring method according to any one of claims 1-7 when executing the program.
14. A computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the monitoring method according to any one of claims 1-7.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110834130.5A CN113558586A (en) | 2021-07-22 | 2021-07-22 | User health monitoring method and device, terminal equipment and storage medium |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110834130.5A CN113558586A (en) | 2021-07-22 | 2021-07-22 | User health monitoring method and device, terminal equipment and storage medium |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN113558586A true CN113558586A (en) | 2021-10-29 |
Family
ID=78166562
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202110834130.5A Pending CN113558586A (en) | 2021-07-22 | 2021-07-22 | User health monitoring method and device, terminal equipment and storage medium |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN113558586A (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114343597A (en) * | 2021-12-29 | 2022-04-15 | 北京小米移动软件有限公司 | Physiological parameter monitoring method and device, keyboard, electronic equipment and storage medium |
Citations (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20030233250A1 (en) * | 2002-02-19 | 2003-12-18 | David Joffe | Systems and methods for managing biological data and providing data interpretation tools |
| US20120296455A1 (en) * | 2011-05-16 | 2012-11-22 | Quentiq AG | Optical data capture of exercise data in furtherance of a health score computation |
| CN103230259A (en) * | 2013-04-18 | 2013-08-07 | 深圳市科曼医疗设备有限公司 | Intelligent alarm device for monitor |
| CN103876718A (en) * | 2014-03-18 | 2014-06-25 | 辛勤 | Health monitoring method based on physiological parameters and system |
| CN105266778A (en) * | 2015-09-18 | 2016-01-27 | 北京交通大学 | Rail transit train worker health condition monitoring system and method |
| CN105380472A (en) * | 2015-11-06 | 2016-03-09 | 陈静 | Pregnant woman pillow and human body state monitoring method and system |
| CN105962918A (en) * | 2016-06-12 | 2016-09-28 | 夏茂 | Human body health evaluation method based on physical health indexes |
| CN106308756A (en) * | 2015-06-29 | 2017-01-11 | 上海卓易科技股份有限公司 | Health information monitoring method and equipment |
| CN108185996A (en) * | 2017-12-27 | 2018-06-22 | 中国科学院深圳先进技术研究院 | Arteries age appraising model construction method and device |
| WO2020133432A1 (en) * | 2018-12-29 | 2020-07-02 | 深圳迈瑞生物医疗电子股份有限公司 | Display method, and monitoring device and system for early warning score |
| CN111358436A (en) * | 2020-03-13 | 2020-07-03 | 芯海科技（深圳）股份有限公司 | Health measurement data processing method, electronic device and storage medium |
| CN112244793A (en) * | 2020-11-02 | 2021-01-22 | 深圳市沃特沃德股份有限公司 | Health monitoring method and device and storage medium |
-
2021
- 2021-07-22 CN CN202110834130.5A patent/CN113558586A/en active Pending
Patent Citations (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20030233250A1 (en) * | 2002-02-19 | 2003-12-18 | David Joffe | Systems and methods for managing biological data and providing data interpretation tools |
| US20120296455A1 (en) * | 2011-05-16 | 2012-11-22 | Quentiq AG | Optical data capture of exercise data in furtherance of a health score computation |
| CN103230259A (en) * | 2013-04-18 | 2013-08-07 | 深圳市科曼医疗设备有限公司 | Intelligent alarm device for monitor |
| CN103876718A (en) * | 2014-03-18 | 2014-06-25 | 辛勤 | Health monitoring method based on physiological parameters and system |
| CN106308756A (en) * | 2015-06-29 | 2017-01-11 | 上海卓易科技股份有限公司 | Health information monitoring method and equipment |
| CN105266778A (en) * | 2015-09-18 | 2016-01-27 | 北京交通大学 | Rail transit train worker health condition monitoring system and method |
| CN105380472A (en) * | 2015-11-06 | 2016-03-09 | 陈静 | Pregnant woman pillow and human body state monitoring method and system |
| CN105962918A (en) * | 2016-06-12 | 2016-09-28 | 夏茂 | Human body health evaluation method based on physical health indexes |
| CN108185996A (en) * | 2017-12-27 | 2018-06-22 | 中国科学院深圳先进技术研究院 | Arteries age appraising model construction method and device |
| WO2020133432A1 (en) * | 2018-12-29 | 2020-07-02 | 深圳迈瑞生物医疗电子股份有限公司 | Display method, and monitoring device and system for early warning score |
| CN111358436A (en) * | 2020-03-13 | 2020-07-03 | 芯海科技（深圳）股份有限公司 | Health measurement data processing method, electronic device and storage medium |
| CN112244793A (en) * | 2020-11-02 | 2021-01-22 | 深圳市沃特沃德股份有限公司 | Health monitoring method and device and storage medium |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114343597A (en) * | 2021-12-29 | 2022-04-15 | 北京小米移动软件有限公司 | Physiological parameter monitoring method and device, keyboard, electronic equipment and storage medium |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| AU2015201213B2 (en) | Measuring blood pressure | |
| JP7113833B2 (en) | Computer-implemented methods and portable devices, and computer program products for analyzing glucose monitoring data indicative of glucose levels in bodily fluids | |
| Sheppard et al. | Predicting out-of-office blood pressure in the clinic (PROOF-BP) derivation and validation of a tool to improve the accuracy of blood pressure measurement in clinical practice | |
| CN108601566B (en) | Mental stress evaluation method and device | |
| US20140206949A1 (en) | Patient mobile computing system and method for exacerbation prediction | |
| US10431343B2 (en) | System and method for interpreting patient risk score using the risk scores and medical events from existing and matching patients | |
| US20160157789A1 (en) | Diagnostic efficiency | |
| US11617545B2 (en) | Methods and systems for adaptable presentation of sensor data | |
| WO2016048520A1 (en) | System method for assessing fitness state via a mobile device | |
| CN113558586A (en) | User health monitoring method and device, terminal equipment and storage medium | |
| CN117158938A (en) | Health monitoring method and device applied to intelligent watch and electronic equipment | |
| CN110689959A (en) | Medical health management method and device | |
| CN117672443A (en) | Physical examination data analysis method and device, electronic equipment and storage medium | |
| EP4137043A1 (en) | Apparatus and method for estimating blood pressure | |
| Richer et al. | Novel human computer interaction principles for cardiac feedback using google glass and Android wear | |
| US20220254502A1 (en) | System, method and apparatus for non-invasive & non-contact monitoring of health racterstics using artificial intelligence (ai) | |
| KR101809149B1 (en) | Apparatus for determining circulatory disease and method thereof | |
| WO2022103410A1 (en) | System and methods for indicating pre-symptomatic adverse conditions in a human | |
| Silva et al. | SenseMyHeart: A cloud service and API for wearable heart monitors | |
| EP3644324A1 (en) | Detecting an ictal of a subject | |
| Setiawan et al. | Electrocardiogram (ECG) Application for Checking Heart Conditions Based on Android | |
| Webster et al. | Heart Snapshot: a broadly validated smartphone measure of VO2max for collection of real world data | |
| CN116849629B (en) | Wearable monitoring terminal and health monitoring intelligent calling system | |
| US20240172945A1 (en) | Apparatus and method for estimating blood pressure | |
| WO2024014875A1 (en) | Method, program and device for improving accuracy of feature extraction for heart rate variability |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |