CN114403825A - Pulse wave signal identification method and device - Google Patents
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Abstract
The embodiment of the invention relates to a pulse wave signal identification method and a device, wherein the method comprises the following steps: calculating corresponding first change rate data according to the time interval data of adjacent pulse wave signals in the pulse wave signal group; identifying the first rate of change data based on a time interval rate of change threshold; in the pulse wave signal group, calculating corresponding second change rate data according to the maximum amplitude difference of adjacent pulse wave signals; identifying second rate of change data according to the maximum magnitude difference rate of change threshold; calculating corresponding third change rate data according to the time width difference of adjacent pulse wave signals in the pulse wave signal group; and identifying the third rate of change data according to the time width rate of change threshold. According to the embodiment of the invention, whether the pulse wave signal group is a group of regular signals or not is judged according to the result of identifying the first, second and third change rate data, and the signal identification capability of the blood pressure measuring equipment can be improved by using the method and the device.
Description
Technical Field
The invention relates to the technical field of signal processing, in particular to a pulse wave signal identification method and device.
Background
The pulse wave is formed by the propagation of the heart along the arterial vessel and blood flow to the periphery, and the propagation speed thereof depends on the elasticity of the artery, the size of the lumen, the density and viscosity of the blood, and the like, and is closely related to the elasticity, caliber and thickness of the arterial wall in particular. Under the condition that the heart is in a normal rhythm, because the heart rate is regular, the related pulse wave is in a regular form; when the heart is in an arrhythmia state (for example, atrial fibrillation), because the heart beat frequency is irregular, the pulse wave related to the heart beat frequency correspondingly takes on an irregular shape. The conventional electronic oscillography measurement method is mainly based on the measurement of regular pulse waves to obtain corresponding blood pressure data, and the reliability and the accuracy of a final measurement result are influenced by excessive irregular pulse waves in the conventional measurement process.
Disclosure of Invention
The present invention is directed to a method, an apparatus, an electronic device, a computer program product, and a computer readable storage medium for identifying pulse wave signals, wherein the method identifies time interval change rate, maximum amplitude difference change rate, and time width change rate data of adjacent pulse wave signals in a current pulse wave signal group, and determines whether the current pulse wave signal group is a set of regular signals. The invention can improve the signal identification capability of the blood pressure measuring equipment, can further refine the classification processing mode of the signals based on the invention, and improves the measurement precision and accuracy of the equipment.
In order to achieve the above object, a first aspect of embodiments of the present invention provides a pulse wave signal identification method, including:
acquiring a pulse wave signal group; the pulse wave signal group includes a plurality of pulse wave signals;
in the pulse wave signal group, sequentially counting time interval data of adjacent pulse wave signals to generate first time interval data; calculating the absolute difference value of the adjacent first time interval data to generate first difference data; selecting the first time interval data with the previous time from the adjacent first time interval data as first reference data; generating first change rate data according to the ratio of the first differential data to the first reference data;
according to a time interval change rate threshold value, performing first regular pulse wave signal identification processing on all the first change rate data to obtain a first identification result;
when the first identification result is regular signal data, sequentially extracting the maximum amplitude data of the pulse wave signals from the pulse wave signal group to generate first amplitude data; calculating the absolute difference value of the adjacent first amplitude data to generate second difference data; selecting the first amplitude data with the earlier time from the adjacent first amplitude data as second reference data; generating second change rate data according to the ratio of the second difference data to the second reference data;
according to the maximum amplitude difference change rate threshold value, performing second regular pulse wave signal identification processing on all the second change rate data to obtain a second identification result;
when the second identification result is the regular signal data, sequentially extracting time width data of the pulse wave signals from the pulse wave signal group to generate first time width data; calculating an absolute difference value of the adjacent first time width data to generate third difference data; selecting the first time width data with the front time from the adjacent first time width data as third reference data; generating third rate-of-change data according to a ratio of the third difference data to the third reference data;
according to the time width change rate threshold value, performing third regular pulse wave signal identification processing on all the third change rate data to obtain a third identification result;
and when the third identification result is the regular pulse wave signal data, generating pulse wave signal identification result which is the regular pulse wave signal data.
Preferably, the method further comprises:
the first recognition result further includes irregular signal data;
the second recognition result further includes the irregular signal data;
the third recognition result further includes the irregular signal data.
Preferably, the performing, according to the time interval change rate threshold, a first regular pulse wave signal identification process on all the first change rate data to obtain a first identification result specifically includes:
when all the first change rate data are smaller than the time interval change rate threshold value, generating the first identification result as the regular signal data;
when all of the first rate of change data is not less than the time interval rate of change threshold, generating the first recognition result as the irregular signal data.
Preferably, the performing, according to the maximum difference change rate threshold, a second regular pulse wave signal identification process on all the second change rate data to obtain a second identification result, specifically including:
when all the second change rate data are smaller than the maximum amplitude difference change rate threshold value, generating the second identification result as the regular signal data;
and when all the second change rate data are not smaller than the maximum amplitude difference change rate threshold value, generating the second identification result as the irregular signal data.
Preferably, the performing, according to the time-width change rate threshold, a third regular pulse wave signal identification process on all the third change rate data to obtain a third identification result specifically includes:
when all the third change rate data are smaller than the time width change rate threshold value, generating the third identification result as the regular signal data;
when all of the third rate-of-change data is not less than the time-width-of-change-rate threshold, generating the third recognition result as the irregular signal data.
Preferably, the method further comprises:
when the first identification result is the irregular signal data, generating that the pulse wave signal identification result is the irregular pulse wave signal data, and exiting the pulse wave signal identification processing flow;
when the second identification result is the irregular pulse wave signal data, generating the pulse wave signal identification result as the irregular pulse wave signal data, and exiting the pulse wave signal identification processing flow;
and when the third identification result is the irregular pulse wave signal data, generating the pulse wave signal identification result as the irregular pulse wave signal data, and exiting the pulse wave signal identification processing flow.
A second aspect of an embodiment of the present invention provides a pulse wave signal identification apparatus, including:
the acquisition module is used for acquiring a pulse wave signal group; the pulse wave signal group includes a plurality of pulse wave signals;
the first identification module is used for sequentially counting the time interval data of the adjacent pulse wave signals in the pulse wave signal group to generate first time interval data; calculating the absolute difference value of the adjacent first time interval data to generate first difference data; selecting the first time interval data with the previous time from the adjacent first time interval data as first reference data; generating first change rate data according to the ratio of the first differential data to the first reference data; according to a time interval change rate threshold value, performing first regular pulse wave signal identification processing on all the first change rate data to obtain a first identification result;
the second identification module is used for sequentially extracting the maximum amplitude data of the pulse wave signals in the pulse wave signal group to generate first amplitude data when the first identification result is regular signal data; calculating the absolute difference value of the adjacent first amplitude data to generate second difference data; selecting the first amplitude data with the earlier time from the adjacent first amplitude data as second reference data; generating second change rate data according to the ratio of the second difference data to the second reference data; according to the maximum amplitude difference change rate threshold value, performing second regular pulse wave signal identification processing on all the second change rate data to obtain a second identification result;
the third identification module is used for sequentially extracting time width data of the pulse wave signals in the pulse wave signal group to generate first time width data when the second identification result is the regular signal data; calculating an absolute difference value of the adjacent first time width data to generate third difference data; selecting the first time width data with the front time from the adjacent first time width data as third reference data; generating third rate-of-change data according to a ratio of the third difference data to the third reference data; according to the time width change rate threshold value, performing third regular pulse wave signal identification processing on all the third change rate data to obtain a third identification result; and when the third identification result is the regular pulse wave signal data, generating pulse wave signal identification result which is the regular pulse wave signal data.
A third aspect of an embodiment of the present invention provides an electronic device, including: a memory, a processor, and a transceiver;
the processor is configured to be coupled to the memory, read and execute instructions in the memory, so as to implement the method steps of the first aspect;
the transceiver is coupled to the processor, and the processor controls the transceiver to transmit and receive messages.
A fourth aspect of embodiments of the present invention provides a computer program product comprising computer program code which, when executed by a computer, causes the computer to perform the method of the first aspect.
A fifth aspect of embodiments of the present invention provides a computer-readable storage medium storing computer instructions that, when executed by a computer, cause the computer to perform the method of the first aspect.
Embodiments of the present invention provide a pulse wave signal identification method, a pulse wave signal identification device, an electronic device, a computer program product, and a computer readable storage medium, which can determine whether a current pulse wave signal group is a set of regular signals by identifying data of a time interval change rate, a maximum amplitude difference change rate, and a time width change rate of adjacent pulse wave signals in the current pulse wave signal group. The invention improves the signal identification capability of the blood pressure measuring equipment, can further refine the classification processing mode of the signals based on the invention, and improves the measuring precision and accuracy of the equipment.
Drawings
Fig. 1 is a schematic diagram of a method for identifying a pulse wave signal according to an embodiment of the present invention;
FIG. 2a is a schematic diagram of a pulse wave signal group and a pulse wave signal according to an embodiment of the present invention;
FIG. 2b is a schematic diagram of a time interval of a pulse wave signal according to an embodiment of the present invention;
FIG. 2c is a schematic diagram illustrating a maximum amplitude of a pulse wave signal according to an embodiment of the present invention;
FIG. 2d is a schematic diagram illustrating a time width of a pulse wave signal according to an embodiment of the present invention;
fig. 3 is a block diagram of a pulse wave signal identification apparatus according to a second embodiment of the present invention;
fig. 4 is a schematic structural diagram of an electronic device according to a third embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention clearer, the present invention will be described in further detail with reference to the accompanying drawings, and it is apparent that the described embodiments are only a part of the embodiments of the present invention, not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The embodiment one of the invention provides a pulse wave signal identification method, after a pulse wave signal group is obtained, whether the current pulse wave signal group is regularly identified is firstly identified by calculating the time interval change rate (first change rate data) between adjacent pulse wave signals; then, whether the current pulse wave signal group is regular or not is identified by calculating the maximum amplitude difference change rate (second change rate data) of adjacent pulse wave signals; then, whether the current pulse wave signal group is regular or not is identified by calculating the time width change rate (third change rate data) of adjacent pulse waves; after all three identification processes are passed, the current pulse wave signal group is determined to be a group of regular pulse wave signals. Compared with a fixed filtering mode, the embodiment of the invention can more flexibly set the accuracy of signal identification and improve the signal identification capability of the blood pressure measuring equipment on the one hand; on the other hand, the obtained pulse wave signal group can be classified, and the blood pressure measuring equipment calls different processing flows to calculate blood pressure data according to classification, so that the measuring precision and accuracy of the equipment are improved.
As shown in fig. 1, which is a schematic diagram of a pulse wave signal identification method according to an embodiment of the present invention, the method mainly includes the following steps:
step 1, acquiring a pulse wave signal group;
wherein, the pulse wave signal group comprises a plurality of pulse wave signals.
Specifically, the method comprises the following steps: the blood pressure measuring equipment can obtain the pulse wave signal group of the patient through directly collecting the patient, can also obtain the pulse wave signal group of the patient through connecting other pulse wave signal collecting equipment, and can also obtain the pulse wave signal group stored in the database through connecting the database. Here, the pulse wave signal group obtained as shown in fig. 2a is a schematic diagram of the pulse wave signal group and the pulse wave signal provided by the embodiment of the present invention, and includes a plurality of continuous pulse wave signals.
Here, the blood pressure measuring device is a terminal device or a server for blood pressure monitoring and measurement, and can perform signal recognition on a pulse wave signal group acquired by local acquisition, can also perform signal recognition on a pulse wave signal group acquired by connecting other pulse wave signal acquisition devices, and can also perform signal recognition on a pulse wave signal group stored in a database acquired by connecting the database.
Step 2, sequentially counting time interval data of adjacent pulse wave signals in the pulse wave signal group to generate first time interval data; calculating the absolute difference value of the adjacent first time interval data to generate first difference data; selecting first time interval data with the earlier time from the adjacent first time interval data as first reference data; and generating first change rate data according to the ratio of the first difference data to the first reference data.
Here, as shown in fig. 2b, which is a schematic diagram of the time intervals of the pulse wave signals according to an embodiment of the present invention, the time intervals of the adjacent pulse wave signals are the time intervals between the maximum amplitude points of the adjacent pulse wave signals; the time interval data is a specific value of this interval.
Here, the first difference data is an absolute difference value obtained by taking an absolute value of a difference obtained by subtracting two adjacent pieces of the first time interval data; the first reference data is the first time interval data which is earlier in time of two adjacent first time interval data for calculating the first difference data; the first change rate data is a ratio of the first difference data to the first reference data, that is, a time interval change rate between adjacent pulse wave signals of the current pulse wave signal group, and the lower the first change rate data is, the lower the probability that the peak point in the wave of the current pulse wave signal group is continuously deformed is (the lower the probability of the occurrence of the irregular characteristic is), whereas the higher the first change rate data is, the higher the probability that the peak point in the wave of the current pulse wave signal group is continuously deformed is (the higher the probability of the occurrence of the irregular characteristic is).
For example, as shown in fig. 2b, the acquired pulse wave signal group includes 4 pulse wave signals: the 1 st to 4 th pulse wave signals, with the time interval between the maximum amplitude points of the adjacent pulse wave signals as the first time interval data, then obtain 3 first time interval data: 1 st to 3 rd first time interval data;
in the 1 st to 3 rd first time interval data, selecting the adjacent first time interval data to perform absolute difference calculation to obtain 2 first difference data:
the 1 st first differential data | the 2 nd first time interval data — the 1 st first time interval data |,
the 2 nd first differential data | the 3 rd first time interval data — the 1 st first time interval data |,
the | | symbol is an absolute value symbol;
corresponding to the 1 st and 2 nd first differential data, 2 first reference data are obtained:
the 1 st first reference data is the first time interval data of the 1 st and 2 nd first time interval data, namely the 1 st first time interval data,
the 2 nd first reference data is the earlier one of the 2 nd and 3 rd first time interval data, namely the 2 nd first time interval data;
obtaining 2 first change rate data according to the 2 first difference data and 2 first reference data corresponding to the 2 first difference data:
the 1 st first change rate data ═ (1 st first differential data/1 st first reference data) × 100%,
the 2 nd first change rate data is (2 nd first differential data/2 nd first reference data) × 100%.
here, the regular pulse wave signal identification operation is performed by comparing whether all the first change rate data satisfy the time interval change rate threshold; the time interval change rate threshold here is a preset empirical value (for example, preset to 10%);
the method specifically comprises the following steps: step 31, when all the first change rate data are smaller than the time interval change rate threshold, generating a first identification result as regular signal data;
when all the first change rate data are smaller than the time interval change rate threshold, the trend that the peak point in the wave of the current pulse wave signal group is continuously deformed is shown to be in a controllable range;
for example, the acquired pulse wave signal group includes 4 pulse wave signals, and the obtained 2 first change rate data are specifically 2% and 3%, and the time interval change rate threshold is 10%, then the generated first identification result should be regular signal data;
and step 32, when all the first change rate data are not smaller than the time interval change rate threshold value, generating a first identification result as irregular signal data.
When all the first change rate data are not smaller than the time interval change rate threshold, the trend that the peak point in the wave of the current pulse wave signal group is continuously deformed is beyond the controllable range;
for example, the acquired pulse wave signal group includes 4 pulse wave signals, 2 pieces of first change rate data are obtained, specifically, 9% and 11%, and the time interval change rate threshold is 10%, then the generated first identification result should be irregular signal data.
And 4, judging whether the first identification result is regular signal data, turning to the step 5 when the first identification result is the regular signal data, and turning to the step 410 when the first identification result is not the regular signal data.
Here, when the first recognition result is the regular signal data, the blood pressure measuring apparatus proceeds to step 5 to perform the next signal recognition processing; when the first identification result is the irregular pulse wave signal data, the blood pressure measuring device proceeds to the error processing flow step 410 to generate the pulse wave signal identification result as the irregular pulse wave signal data, and exits from the current pulse wave signal identification processing flow.
Step 5, sequentially extracting the maximum amplitude data of the pulse wave signals from the pulse wave signal group to generate first amplitude data; calculating the absolute difference value of the adjacent first amplitude data to generate second difference data; selecting first amplitude data with earlier time from adjacent first amplitude data as second reference data; second rate of change data is generated based on a ratio of the second difference data to the second reference data.
Here, as shown in fig. 2c, which is a schematic diagram illustrating the maximum amplitude of the pulse wave signal according to an embodiment of the present invention, the first amplitude data is the maximum amplitude data of each pulse wave; the second difference data is the absolute difference value of the adjacent first amplitude data, namely the maximum amplitude absolute difference value of the adjacent pulse wave signals; the second reference data is the first amplitude data which is earlier in time of two adjacent first amplitude data for calculating the second difference data; the second change rate data is a ratio of the second difference data to the second reference data, that is, a maximum amplitude difference change rate between adjacent pulse wave signals of the current pulse wave signal group, and the lower the second change rate data is, the lower the probability that the amplitude of the current pulse wave signal group is continuously deformed is (the lower the probability of occurrence of an irregular characteristic), whereas the higher the second change rate data is, the higher the probability that the amplitude of the current pulse wave signal group is continuously deformed is (the higher the probability of occurrence of an irregular characteristic).
For example, as shown in fig. 2c, the acquired pulse wave signal group includes 4 pulse wave signals: extracting the maximum amplitude data of the 1 st to 4 th pulse wave signals to obtain 4 first amplitude data: 1 st to 4 th first amplitude data;
in the 1 st to 4 th first amplitude data, selecting the adjacent first amplitude data to calculate the absolute difference value, and obtaining 3 second difference data:
the 1 st second differential data ═ 2 nd first amplitude data — the 1 st first amplitude data |,
the 2 nd second differential data ═ 3 rd first amplitude data — 2 nd first amplitude data |, the 3 rd second differential data ═ 4 th first amplitude data — 3 rd first amplitude data |;
corresponding to the 1 st to 3 rd second differential data, 3 second reference data are obtained:
the 1 st second reference data is the temporally previous one of the 1 st and 2 nd first amplitude data, that is, the 1 st first amplitude data,
the 2 nd second reference data is the temporally previous one of the 2 nd and 3 rd first amplitude data, that is, the 2 nd first amplitude data,
the 3 rd second reference data is the first data in time from the 3 rd and 4 th first amplitude data, namely the 3 rd first amplitude data;
obtaining 3 second change rate data according to the 3 second difference data and the 3 second reference data corresponding to the 3 second difference data:
the 1 st second change rate data ═ (1 st second differential data/1 st second reference data) × 100%,
the 2 nd second change rate data ═ (2 nd second differential data/2 nd second reference data) × 100%,
the 3 rd second change rate data is (3 rd second differential data/3 rd second reference data) × 100%.
here, regular pulse wave signal identification operation is performed by comparing whether all the second change rate data satisfy the maximum amplitude difference change rate threshold; the maximum amplitude difference change rate threshold here is a preset empirical value (for example, preset to 50%);
the method specifically comprises the following steps: step 61, when all the second change rate data are smaller than the maximum amplitude difference change rate threshold value, generating a second identification result as regular signal data;
when all the second change rate data are smaller than the maximum amplitude difference change rate threshold value, the trend that the amplitude of the current pulse wave signal group is continuously deformed is shown to be in a controllable range;
for example, the acquired pulse wave signal group includes 4 pulse wave signals, 3 second change rate data are obtained, specifically 7%, 3% and 3%, and the maximum amplitude difference change rate threshold is 50%, then the generated second identification result should be regular signal data;
and 62, when all the second change rate data are not smaller than the maximum amplitude difference change rate threshold value, generating a second identification result as irregular signal data.
When all the second change rate data are not smaller than the maximum amplitude difference change rate threshold, the trend that the amplitude of the current pulse wave signal group is continuously deformed is beyond the controllable range;
for example, the acquired pulse wave signal group includes 4 pulse wave signals, 3 second change rate data are obtained, specifically 15%, 40%, and 51%, and the maximum amplitude difference change rate threshold is 50%, then the generated second identification result should be irregular signal data.
And 7, judging whether the second identification result is regular signal data, turning to the step 8 when the second identification result is the regular signal data, and turning to the step 410 when the second identification result is not the regular signal data.
Here, when the second recognition result is the regular signal data, the blood pressure measuring apparatus proceeds to step 8 to perform the next signal recognition processing; when the second recognition result is irregular signal data, the blood pressure measurement device proceeds to the error processing flow step 410.
Here, as shown in fig. 2d, which is a schematic diagram of the time width of the pulse wave signal according to an embodiment of the present invention, the first time width data is the time interval from the starting point to the ending point of the pulse wave signal; the third difference data is the absolute difference of the adjacent first time width data, namely the absolute difference of the time width data of the adjacent pulse wave signals; the third reference data is the first time width data that is earlier in time of two adjacent first time width data for which the third differential data is calculated; the third change rate data is a ratio of the third difference data to the third reference data, that is, a time width change rate between adjacent pulse wave signals of the current pulse wave signal group, and the lower the third change rate data is, the lower the probability that the width of the current pulse wave signal group is continuously deformed is (the lower the probability of occurrence of an irregular characteristic), whereas the higher the third change rate data is, the higher the probability that the width of the current pulse wave signal group is continuously deformed is (the higher the probability of occurrence of an irregular characteristic).
For example, as shown in fig. 2d, the acquired set of pulse wave signals includes 4 pulse wave signals: 1 st to 4 th pulse wave signals, extracting time width data of the 1 st to 4 th pulse wave signals to obtain 4 first time width data: 1 st to 4 th first time width data;
selecting adjacent first time width data from the 1 st to 4 th first time width data to perform absolute difference calculation to obtain 3 third difference data:
the 1 st third differential data | the 2 nd first time width data — the 1 st first time width data |,
the 2 nd third differential data | the 3 rd first time width data — the 2 nd first time width data |,
third difference data of 3 rd ═ 4 th first time width data — 3 rd first time width data |;
corresponding to the 1 st to 3 rd third differential data, 3 third reference data are obtained:
the 1 st third reference data is the first time-series one of the 1 st and 2 nd first time width data, that is, the 1 st first time width data,
the 2 nd third reference data is the temporally previous one of the 2 nd and 3 rd first time width data, that is, the 2 nd first time width data,
the 3 rd third reference data is the first time data in the 3 rd and 4 th first time width data, namely the 3 rd first time width data;
obtaining 3 third change rate data according to the 3 third difference data and 3 third reference data corresponding to the 3 third difference data:
the 1 st third change rate data ═ (1 st third differential data/1 st third reference data) × 100%,
the 2 nd third change rate data ═ (2 nd third differential data/2 nd third reference data) × 100%,
the 3 rd third change rate data ═ (3 rd third differential data/3 rd third reference data) × 100%.
Step 9, according to the time width change rate threshold, performing third regular pulse wave signal identification processing on all third change rate data to obtain a third identification result;
here, the regular pulse wave signal identification operation is performed by comparing whether all the third change rate data satisfy the time width change rate threshold; the time width change rate threshold here is a preset empirical value (for example, preset to 50%);
the method specifically comprises the following steps: step 91, when all the third change rate data are smaller than the time width change rate threshold, generating a third identification result as regular signal data;
when all the third change rate data are smaller than the time width change rate threshold, the trend that the width of the current pulse wave signal group is continuously deformed is shown to be in a controllable range;
for example, the acquired pulse wave signal group includes 4 pulse wave signals, and 3 third change rate data are obtained, specifically 5%, 2%, and 1%, and the time width change rate threshold is 50%, then the generated third identification result should be regular signal data;
and step 92, when all the third change rate data are not smaller than the time width change rate threshold, generating a third identification result as irregular signal data.
When all the third change rate data are not less than the time width change rate threshold, it indicates that the trend of the current pulse wave signal group with continuous width deformation exceeds the controllable range;
for example, if the acquired pulse wave signal group includes 4 pulse wave signals, and 3 third change rate data sets of 15%, 35%, and 55% are obtained, and the time width change rate threshold is 50%, the generated third identification result should be irregular signal data.
Here, when the third recognition result is the regular signal data, the blood pressure measuring apparatus continues to perform the setting operation of the final recognition result in step 11; when the third recognition result is the irregular signal data, the blood pressure measurement device proceeds to the error processing flow step 410.
And 11, generating the pulse wave signal identification result as regular pulse wave signal data.
Here, the pulse wave signal identification result is final result data of identification of the current pulse wave signal group by the blood pressure measurement device; when the third identification result is the regular signal data, it indicates that the blood pressure measuring device has completed all identification processes on the current pulse wave signal group and all the identification results of the regular signal data are obtained, so the pulse wave signal identification result should be the regular pulse wave signal data.
After the blood pressure measurement device confirms that the pulse wave signal identification result is the regular pulse wave signal data, the current pulse wave signal group can be further marked as the regular signal type, then a blood pressure measurement processing flow corresponding to the regular signal type is called, the measurement and calculation of the blood pressure data are carried out on the current pulse wave signal group, and the blood pressure related data (such as average pressure data, systolic pressure data and diastolic pressure data) of the current pulse wave signal group are obtained.
Step 410, generating the pulse wave signal identification result as irregular pulse wave signal data, and exiting the pulse wave signal identification processing flow.
Here, the pulse wave signal identification result is final result data of identification of the current pulse wave signal group by the blood pressure measurement device; the reason for the execution step jumping to this point is various, and it is common that the trend of continuous deformation of peak points in the current pulse wave signal group exceeds the controllable range, or the trend of continuous deformation of amplitude of the current pulse wave signal group exceeds the controllable range, or the trend of continuous deformation of width of the current pulse wave signal group exceeds the controllable range, and so on.
When the problem occurs, the blood pressure measuring equipment sets the identification result of the current pulse wave signal group as irregular pulse wave signal data and exits from the currently executed pulse wave signal identification processing flow; then, the blood pressure measuring equipment can display the prompt message of the unreliable signal; the current pulse wave signal group can be further marked as an irregular signal type, then a blood pressure measurement processing flow corresponding to the irregular signal type is called, blood pressure data measurement and estimation are carried out on the current pulse wave signal group, and blood pressure related data (such as average pressure data, systolic pressure data and diastolic pressure data) of the current pulse wave signal group are obtained.
Fig. 3 is a block diagram of a pulse wave signal identification apparatus according to a second embodiment of the present invention, where the apparatus may be the terminal device or the server described in the foregoing embodiment, or may be an apparatus that enables the terminal device or the server to implement the method according to the second embodiment of the present invention, and for example, the apparatus may be an apparatus or a chip system of the terminal device or the server. As shown in fig. 3, the apparatus includes:
the acquisition module 301 is configured to acquire a pulse wave signal group; wherein, the pulse wave signal group comprises a plurality of pulse wave signals.
The first identification module 302 is configured to sequentially count time interval data of adjacent pulse wave signals in the pulse wave signal group, and generate first time interval data; calculating the absolute difference value of the adjacent first time interval data to generate first difference data; selecting first time interval data with the earlier time from the adjacent first time interval data as first reference data; generating first change rate data according to the ratio of the first difference data to the first reference data; and according to the time interval change rate threshold, performing first regular pulse wave signal identification processing on all the first change rate data to obtain a first identification result.
In a specific implementation manner provided in this embodiment, the first identifying module 302 is specifically configured to: when all the first change rate data are smaller than the time interval change rate threshold value, generating a first identification result as regular signal data; when all of the first rate-of-change data is not less than the time interval rate-of-change threshold, generating the first recognition result as irregular signal data.
The first identification module 302 is further configured to generate a pulse wave signal identification result as irregular pulse wave signal data when the first identification result is the irregular signal data, and exit from the pulse wave signal identification processing procedure.
The second identification module 303 is configured to, when the first identification result is the regular signal data, sequentially extract maximum amplitude data of the pulse wave signals in the pulse wave signal group to generate first amplitude data; calculating the absolute difference value of the adjacent first amplitude data to generate second difference data; selecting first amplitude data with earlier time from adjacent first amplitude data as second reference data; generating second change rate data according to the ratio of the second difference data to the second reference data; and according to the maximum amplitude difference change rate threshold, performing second regular pulse wave signal identification processing on all second change rate data to obtain a second identification result.
In another specific implementation manner provided in this embodiment, the second identifying module 303 is specifically configured to: when all the second change rate data are smaller than the maximum amplitude difference change rate threshold value, generating a second identification result as regular signal data; when all of the second change rate data are not less than the maximum amplitude difference change rate threshold, generating the second recognition result as irregular signal data.
The second identification module 303 is further configured to generate a pulse wave signal identification result as irregular pulse wave signal data when the second identification result is the irregular signal data, and exit from the pulse wave signal identification processing procedure.
The third identification module 304 is configured to, when the second identification result is the regular signal data, sequentially extract time width data of the pulse wave signal in the pulse wave signal group to generate first time width data; calculating an absolute difference value of adjacent first time width data to generate third difference data; selecting first time width data with the earlier time from the adjacent first time width data as third reference data; generating third rate-of-change data according to a ratio of the third difference data to the third reference data; according to the time width change rate threshold, performing third regular pulse wave signal identification processing on all third change rate data to obtain a third identification result; and when the third identification result is the regular signal data, generating the pulse wave signal identification result as the regular pulse wave signal data.
In another specific implementation manner provided in this embodiment, the third identifying module 304 is specifically configured to: when all the third change rate data are smaller than the time width change rate threshold value, generating a third identification result as regular signal data; when all of the third change rate data are not less than the time-width change rate threshold value, a third recognition result is generated as irregular signal data.
The third identification module 304 is further configured to generate a pulse wave signal identification result as irregular pulse wave signal data when the third identification result is the irregular signal data, and exit the pulse wave signal identification processing procedure.
The pulse wave signal identification device provided by the embodiment of the invention can execute the method steps in the method embodiments, and the implementation principle and the technical effect are similar, so that the details are not repeated.
It should be noted that the division of the modules of the above apparatus is only a logical division, and the actual implementation may be wholly or partially integrated into one physical entity, or may be physically separated. And these modules can be realized in the form of software called by processing element; or may be implemented entirely in hardware; and part of the modules can be realized in the form of calling software by the processing element, and part of the modules can be realized in the form of hardware. For example, the obtaining module may be a processing element separately set up, or may be implemented by being integrated in a chip of the apparatus, or may be stored in a memory of the apparatus in the form of program code, and a processing element of the apparatus calls and executes the functions of the determining module. Other modules are implemented similarly. In addition, all or part of the modules can be integrated together or can be independently realized. The processing element described herein may be an integrated circuit having signal processing capabilities. In implementation, each step of the above method or each module above may be implemented by an integrated logic circuit of hardware in a processor element or an instruction in the form of software.
For example, the above modules may be one or more integrated circuits configured to implement the above methods, such as: one or more Application Specific Integrated Circuits (ASICs), or one or more Digital Signal Processors (DSPs), or one or more Field Programmable Gate Arrays (FPGAs), etc. For another example, when some of the above modules are implemented in the form of a Processing element scheduler code, the Processing element may be a general-purpose processor, such as a Central Processing Unit (CPU) or other processor that can invoke the program code. As another example, these modules may be integrated together and implemented in the form of a System-on-a-chip (SOC).
In the above embodiments, the implementation may be wholly or partially realized by software, hardware, firmware, or any combination thereof. When implemented in software, may be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When loaded and executed on a computer, cause the processes or functions described in accordance with the embodiments of the invention to occur, in whole or in part. The computer may be a general purpose computer, a special purpose computer, a network of computers, or other programmable device. The computer instructions may be stored on a computer readable storage medium or transmitted from one computer readable storage medium to another, for example, from one website, computer, server, or data center to another website, computer, server, or data center via wire (e.g., coaxial cable, fiber optics, Digital Subscriber Line (DSL)), or wireless (e.g., infrared, wireless, bluetooth, microwave, etc.). DVD), or semiconductor media (e.g., Solid State Disk (SSD)), etc.
Fig. 4 is a schematic structural diagram of an electronic device according to a third embodiment of the present invention. The electronic device may be the terminal device or the server, or may be a terminal device or a server connected to the terminal device or the server and implementing the method according to the embodiment of the present invention. As shown in fig. 4, the electronic device may include: a processor 41 (e.g., CPU), memory 42, transceiver 43; the transceiver 43 is coupled to the processor 41, and the processor 41 controls the transceiving action of the transceiver 43. Various instructions may be stored in memory 42 for performing various processing functions and implementing the methods and processes provided in the above-described embodiments of the present invention. Preferably, the electronic device according to an embodiment of the present invention further includes: a power supply 44, a system bus 45, and a communication port 46. The system bus 45 is used to implement communication connections between the elements. The communication port 46 is used for connection communication between the electronic device and other peripherals.
The system bus mentioned in fig. 4 may be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus or the like. The system bus may be divided into an address bus, a data bus, a control bus, and the like. For ease of illustration, only one thick line is shown, but this does not mean that there is only one bus or one type of bus. The communication interface is used for realizing communication between the database access device and other equipment (such as a client, a read-write library and a read-only library). The Memory may include a Random Access Memory (RAM) and may also include a Non-Volatile Memory (Non-Volatile Memory), such as at least one disk Memory.
The Processor may be a general-purpose Processor, including a central processing unit CPU, a Network Processor (NP), and the like; but also a digital signal processor DSP, an application specific integrated circuit ASIC, a field programmable gate array FPGA or other programmable logic device, discrete gate or transistor logic, discrete hardware components.
It should be noted that the embodiment of the present invention also provides a computer-readable storage medium, which stores instructions that, when executed on a computer, cause the computer to execute the method and the processing procedure provided in the above-mentioned embodiment.
The embodiment of the invention also provides a chip for running the instructions, and the chip is used for executing the method and the processing process provided by the embodiment.
Embodiments of the present invention also provide a program product, which includes a computer program stored in a storage medium, from which the computer program can be read by at least one processor, and the at least one processor executes the methods and processes provided in the embodiments.
Embodiments of the present invention provide a pulse wave signal identification method, a pulse wave signal identification device, an electronic device, a computer program product, and a computer readable storage medium, which can determine whether a pulse wave signal group is a set of regular signals by identifying a time interval change rate, a maximum amplitude difference change rate, and a time width change rate of adjacent pulse wave signals in the pulse wave signal group. The invention improves the signal identification capability of the blood pressure measuring equipment, can further refine the classification processing mode of the signals based on the invention, and improves the measuring precision and accuracy of the equipment.
Those of skill would further appreciate that the various illustrative components and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, computer software, or combinations of both, and that the various illustrative components and steps have been described above generally in terms of their functionality in order to clearly illustrate this interchangeability of hardware and software. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. 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 invention.
The steps of a method or algorithm described in connection with the embodiments disclosed herein may be embodied in hardware, a software module executed by a processor, or a combination of the two. A software module may reside in Random Access Memory (RAM), memory, Read Only Memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art.
The above-mentioned embodiments are intended to illustrate the objects, technical solutions and advantages of the present invention in further detail, and it should be understood that the above-mentioned embodiments are merely exemplary embodiments of the present invention, and are not intended to limit the scope of the present invention, and any modifications, equivalent substitutions, improvements and the like made within the spirit and principle of the present invention should be included in the scope of the present invention.
Claims (10)
1. A pulse wave signal identification method, characterized by comprising:
acquiring a pulse wave signal group; the pulse wave signal group includes a plurality of pulse wave signals;
in the pulse wave signal group, sequentially counting time interval data of adjacent pulse wave signals to generate first time interval data; calculating the absolute difference value of the adjacent first time interval data to generate first difference data; selecting the first time interval data with the previous time from the adjacent first time interval data as first reference data; generating first change rate data according to the ratio of the first differential data to the first reference data;
according to a time interval change rate threshold value, performing first regular pulse wave signal identification processing on all the first change rate data to obtain a first identification result;
when the first identification result is regular signal data, sequentially extracting the maximum amplitude data of the pulse wave signals from the pulse wave signal group to generate first amplitude data; calculating the absolute difference value of the adjacent first amplitude data to generate second difference data; selecting the first amplitude data with the earlier time from the adjacent first amplitude data as second reference data; generating second change rate data according to the ratio of the second difference data to the second reference data;
according to the maximum amplitude difference change rate threshold value, performing second regular pulse wave signal identification processing on all the second change rate data to obtain a second identification result;
when the second identification result is the regular signal data, sequentially extracting time width data of the pulse wave signals from the pulse wave signal group to generate first time width data; calculating an absolute difference value of the adjacent first time width data to generate third difference data; selecting the first time width data with the front time from the adjacent first time width data as third reference data; generating third rate-of-change data according to a ratio of the third difference data to the third reference data;
according to the time width change rate threshold value, performing third regular pulse wave signal identification processing on all the third change rate data to obtain a third identification result;
and when the third identification result is the regular pulse wave signal data, generating pulse wave signal identification result which is the regular pulse wave signal data.
2. The pulse wave signal identification method according to claim 1, further comprising:
the first recognition result further includes irregular signal data;
the second recognition result further includes the irregular signal data;
the third recognition result further includes the irregular signal data.
3. The method for recognizing a pulse wave signal according to claim 1 or 2, wherein the performing a first regular pulse wave signal recognition process on all the first change rate data according to a time interval change rate threshold to obtain a first recognition result specifically includes:
when all the first change rate data are smaller than the time interval change rate threshold value, generating the first identification result as the regular signal data;
when all of the first rate of change data is not less than the time interval rate of change threshold, generating the first recognition result as the irregular signal data.
4. The method for pulse wave signal identification according to claim 1 or 2, wherein the performing a second regular pulse wave signal identification process on all the second change rate data according to a maximum amplitude difference change rate threshold to obtain a second identification result specifically includes:
when all the second change rate data are smaller than the maximum amplitude difference change rate threshold value, generating the second identification result as the regular signal data;
and when all the second change rate data are not smaller than the maximum amplitude difference change rate threshold value, generating the second identification result as the irregular signal data.
5. The method for recognizing a pulse wave signal according to claim 1 or 2, wherein the performing a third regular pulse wave signal recognition process on all the third change rate data according to a time width change rate threshold to obtain a third recognition result specifically includes:
when all the third change rate data are smaller than the time width change rate threshold value, generating the third identification result as the regular signal data;
when all of the third rate-of-change data is not less than the time-width-of-change-rate threshold, generating the third recognition result as the irregular signal data.
6. The pulse wave signal identification method according to claim 1 or 2, characterized by further comprising:
when the first identification result is the irregular signal data, generating that the pulse wave signal identification result is the irregular pulse wave signal data, and exiting the pulse wave signal identification processing flow;
when the second identification result is the irregular pulse wave signal data, generating the pulse wave signal identification result as the irregular pulse wave signal data, and exiting the pulse wave signal identification processing flow;
and when the third identification result is the irregular pulse wave signal data, generating the pulse wave signal identification result as the irregular pulse wave signal data, and exiting the pulse wave signal identification processing flow.
7. A pulse wave signal recognition apparatus, comprising:
the acquisition module is used for acquiring a pulse wave signal group; the pulse wave signal group includes a plurality of pulse wave signals;
the first identification module is used for sequentially counting the time interval data of the adjacent pulse wave signals in the pulse wave signal group to generate first time interval data; calculating the absolute difference value of the adjacent first time interval data to generate first difference data; selecting the first time interval data with the previous time from the adjacent first time interval data as first reference data; generating first change rate data according to the ratio of the first differential data to the first reference data; according to a time interval change rate threshold value, performing first regular pulse wave signal identification processing on all the first change rate data to obtain a first identification result;
the second identification module is used for sequentially extracting the maximum amplitude data of the pulse wave signals in the pulse wave signal group to generate first amplitude data when the first identification result is regular signal data; calculating the absolute difference value of the adjacent first amplitude data to generate second difference data; selecting the first amplitude data with the earlier time from the adjacent first amplitude data as second reference data; generating second change rate data according to the ratio of the second difference data to the second reference data; according to the maximum amplitude difference change rate threshold value, performing second regular pulse wave signal identification processing on all the second change rate data to obtain a second identification result;
the third identification module is used for sequentially extracting time width data of the pulse wave signals in the pulse wave signal group to generate first time width data when the second identification result is the regular signal data; calculating an absolute difference value of the adjacent first time width data to generate third difference data; selecting the first time width data with the front time from the adjacent first time width data as third reference data; generating third rate-of-change data according to a ratio of the third difference data to the third reference data; according to the time width change rate threshold value, performing third regular pulse wave signal identification processing on all the third change rate data to obtain a third identification result; and when the third identification result is the regular pulse wave signal data, generating pulse wave signal identification result which is the regular pulse wave signal data.
8. An electronic device, comprising: a memory, a processor, and a transceiver;
the processor is used for being coupled with the memory, reading and executing the instructions in the memory to realize the method steps of any one of claims 1-6;
the transceiver is coupled to the processor, and the processor controls the transceiver to transmit and receive messages.
9. A computer program product, characterized in that the computer program product comprises computer program code which, when executed by a computer, causes the computer to perform the method of any of claims 1-6.
10. A computer-readable storage medium having stored thereon computer instructions which, when executed by a computer, cause the computer to perform the method of any of claims 1-6.
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