CN114041766B - Blood pressure measurement optimizing system - Google Patents
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- 238000009530 blood pressure measurement Methods 0.000 title claims abstract description 49
- 230000036772 blood pressure Effects 0.000 claims abstract description 102
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- 230000006837 decompression Effects 0.000 claims abstract description 9
- 230000035487 diastolic blood pressure Effects 0.000 claims description 16
- 238000005259 measurement Methods 0.000 claims description 16
- 238000005457 optimization Methods 0.000 claims description 13
- 230000035488 systolic blood pressure Effects 0.000 claims description 13
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- 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
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Abstract
The invention discloses a blood pressure measurement optimizing system, which is used for: acquiring a pressure mixing curve in the inflation process, extracting pulse signals in the pressure mixing curve, and processing to obtain an envelope curve of the variation trend of the pulse signals; calculating blood pressure based on the envelope curve to obtain a blood pressure value; analyzing based on the pulse signals to obtain quality evaluation coefficients of the pulse signals; comparing the quality evaluation coefficient with a set threshold value, and determining whether to use the blood pressure value calculated by the pressurization and whether to set a soft threshold value for a target pressure value; and comparing the quality evaluation coefficient with a set threshold value to determine whether to perform blood pressure calculation by a decompression method. The invention can improve the accuracy of blood pressure measurement.
Description
Technical Field
The invention relates to the field of blood pressure measurement, in particular to a blood pressure measurement optimizing system.
Background
When blood flows in a blood vessel, the side pressure on the wall of the blood vessel is called blood pressure, which is often referred to as arterial blood pressure or systemic blood pressure, and is an important vital sign. Blood pressure plays a vital role in rehabilitation observation after healing, treatment effect feedback, disease judgment and the like.
The current blood pressure measurement method can be divided into two main types, namely, an invasive measurement method and a non-invasive measurement method, wherein the invasive measurement method is a gold standard for blood pressure measurement, but is not favored by the public due to the complex operation, poor repeatability and high operation cost of the invasive measurement method and the easy occurrence of wound infection, bleeding, pain, thrombus formation, air embolism and other consequences of a tested person in the blood pressure measurement process. The main principle of the current medical or household electronic sphygmomanometer is that the arterial pressure of a human body is closed firstly, then at least two effective pulse signals are obtained at each deflation step in a step deflation mode, the amplitude trend of the pulse signals is constructed through envelope fitting, and finally the calculation of blood pressure is completed through fitting an envelope curve.
The traditional blood pressure calculation method is to pressurize the cuff and then measure the cuff in the deflation process, and has two disadvantages: (1) a long blood pressure measurement period; (2) poor measurement comfort.
The oscillometric method is mainly divided into two parts in the process of blood pressure calculation: (1) blocking blood flow under pressure; (2) measuring blood pressure under reduced pressure.
The system will initialize or set a target pressure according to the last blood pressure measurement result during the pressurization process, if the initialized target pressure value is 160mmHg-180mmHg for the first time, if the blood pressure result has been measured, the next inflation pressure target set value is 30mmHg-40mmHg plus the last systolic pressure, and this mode we call the target pressure hard threshold setting mode. Taking blood pressure measurements in this way reduces their efficiency of measurement in several cases: (1) If the blood pressure of the tested person is relatively low in the initial process, the setting mode of the target pressure hard threshold is adopted to reduce the blood pressure measurement efficiency and influence the feeling of the tested person at the same time, namely the false pressurization in the initial process;
(2) In the process of measuring blood pressure in a hospital, a blood pressure measuring device and a patient are generally one-to-many, and a target pressure hard threshold setting mode cannot quickly respond between different patient switches, namely differential setting cannot be performed;
(3) In the process of blood pressure measurement, if the tested person moves, the system can possibly recognize the movement interference as a pulse signal at the moment, and then the system can consider that the current pressure value can not completely close the artery, and the situation of false pressurization occurs, namely, poor movement resistance.
If a movement occurs during the reduced pressure measurement, the blood pressure measurement accuracy may be reduced. The following we analyze according to where the motion occurs:
(1) The cuff pressure is greater than the actual systolic pressure stage, and the motion can generate pulse-like signals at the moment, so that the system can misuse the pulse signals at the moment to further cause the calculated systolic pressure to be larger;
(2) The cuff pressure is in a stage between the systolic pressure and the average pressure, and at the moment, the average pressure calculation is higher due to the movement, so that the measurement accuracy of the systolic pressure and the diastolic pressure is affected;
(3) The cuff pressure is in a stage between the diastolic pressure and the average pressure, and at the moment, the average pressure calculation is lower due to the movement, so that the measurement accuracy of the systolic pressure and the diastolic pressure is affected;
(4) The cuff pressure is less than the diastolic phase, and the occurrence of motion may cause the diastolic calculation to be low.
Disclosure of Invention
The present invention aims to solve at least one of the technical problems existing in the prior art. Therefore, the invention provides a blood pressure measurement optimization method which can improve the blood pressure measurement precision.
The invention also provides a blood pressure measurement optimizing system.
The invention also provides a computer readable storage medium for implementing the blood pressure measurement optimization method.
An embodiment of a blood pressure measurement optimization method according to the first aspect of the present invention comprises the steps of: acquiring a pressure mixing curve in the inflation process, extracting pulse signals in the pressure mixing curve, and processing to obtain an envelope curve of the variation trend of the pulse signals; calculating blood pressure based on the envelope curve to obtain a blood pressure value; analyzing based on the pulse signals to obtain quality evaluation coefficients of the pulse signals; comparing the quality evaluation coefficient with a set threshold value, and determining whether to use the blood pressure value calculated by the pressurization and whether to set a soft threshold value for a target pressure value; and comparing the quality evaluation coefficient with a set threshold value to determine whether to perform blood pressure calculation by a decompression method.
The blood pressure measurement optimization method provided by the embodiment of the invention has at least the following beneficial effects: according to the embodiment of the invention, the calculation of the blood pressure and the quality evaluation of the pulse signal are completed in a relevant mode such as signal processing in the inflation stage, whether the blood pressure value is required to be calculated in a deflation measurement mode is finally determined according to the comparison between the quality evaluation factor and the threshold value, and the target pressure is set in a setting mode of the target pressure soft threshold value, so that the accurate control of the inflation target pressure is achieved, and the blood pressure measurement efficiency is improved.
According to some embodiments of the invention, comparing the quality assessment factor with a set threshold value, determining whether to use the blood pressure value calculated for the present pressurization and whether to soft threshold the target pressure value comprises: obtaining two set thresholds through the quality evaluation coefficient, wherein the two set thresholds comprise a first threshold and a second threshold, and the first threshold is smaller than the second threshold; when the quality evaluation coefficient is smaller than the first threshold value, setting a hard threshold value for a target pressure value; when the quality evaluation coefficient is larger than or equal to the first threshold value and smaller than or equal to the second threshold value, setting a soft threshold value for a target pressure value; and when the quality evaluation coefficient is larger than the second threshold value, performing soft threshold setting on a target pressure value and outputting the blood pressure value calculated by pressurization as a blood pressure measurement result.
According to some embodiments of the invention, when the quality assessment coefficient is less than or equal to the second threshold, determining to perform a depressurization blood pressure calculation includes: and acquiring a pulse signal in the deflation process, and analyzing and obtaining a blood pressure value measured by a decompression method based on the pulse signal.
According to some embodiments of the invention, the reduced pressure method blood pressure calculation comprises: during deflation, an anti-motion strategy is employed for motion disturbance, comprising: if the motion signal is in a state that the pulse is completely closed, between the systolic pressure and the diastolic pressure or between the average pressure and the diastolic pressure, giving a motion prompt to prompt the tested person to stop the motion, then continuing to deflate, and identifying the motion signal as an invalid signal not serving as a basis for the subsequent blood pressure calculation; if the position of the motion signal is smaller than the diastolic pressure, the motion signal is identified as an invalid signal and is not used as the basis for the subsequent blood pressure calculation, and the blood pressure measurement is directly ended to output a blood pressure calculation result. The embodiment improves the blood pressure measurement precision in the deflation stage, and because the blood pressure value is already calculated in the inflation stage by a related signal processing mode, whether the pulse signal is generated for movement or not can be directly and reversely deduced in the subsequent deflation stage, thereby improving the blood pressure measurement precision in the deflation stage.
According to some embodiments of the invention, the soft threshold setting comprises: and feeding the blood pressure value back to a pressure control system, and setting a target pressure value according to the blood pressure value by the pressure control system. In the embodiment, the target pressure is set by using a setting mode of the target pressure soft threshold value, so that the efficiency of blood pressure measurement is improved. In order to ensure that the target inflation pressure can be accurately determined each time, a relevant signal processing means is adopted to extract pulse signals in the inflation stage, firstly, the quality judgment is carried out on the extracted pulse signals, then, the blood pressure value is determined through an amplitude coefficient method, a qualitative method and a pressure envelope curve inflection point method, the calculated blood pressure value is fed back to a pressure control system, and finally, the setting of the target pressure value is finished, so that the accurate control of the inflation target pressure is achieved, and the efficiency of blood pressure calculation is improved.
According to some embodiments of the invention, the method further comprises excluding motion disturbances during inflation, comprising: when the target pressure value is not reached, motion occurs and a pulse-like signal is generated, and the signal type of the pulse-like signal is determined according to the position where the pulse-like signal occurs and the intensity of the pulse-like signal; if the pulse signal is the pulse signal, continuing to carry out the subsequent measurement step; if the pressure reaches the target pressure set in a soft threshold mode, determining a blood pressure value or a deflation measurement calculated directly by using a pressurizing mode according to the range of the quality evaluation coefficient at the moment; if the target pressure set by the soft threshold has not been reached, the inflation is continued and then a subsequent measurement operation is performed. In the embodiment, the anti-motion capability of the system is improved in the inflation process, the blood pressure value is calculated in a pressurizing mode, the position of the similar pulse wave is judged, whether the pulse wave is a real pulse wave or not is judged, and then the system performs next operation to determine whether to perform next inflation or directly perform blood pressure measurement in the deflation stage.
According to some embodiments of the present invention, extracting the pulse signal in the pressure mixing curve and processing to obtain an envelope curve of the trend of the pulse signal includes: extracting pulse signals in the pressure mixing curve in a related time domain or frequency domain mode, and extracting time domain and frequency domain characteristics of the pulse signals in a time domain or frequency domain or time domain and frequency domain combined calculation mode after obtaining the pulse signals; and operating the characteristics of the pulse signals in a linear or nonlinear interpolation mode to finally obtain an envelope curve of the variation trend of the pulse signals.
According to some embodiments of the invention, analyzing the quality assessment coefficient of the pulse signal based on the pulse signal comprises: analyzing by a mode of combining a time domain or a frequency domain or a time domain and a frequency domain; the time domain mode comprises the following steps: analyzing pulse characteristics of the pulse signals, respectively calculating the peak amplitude variation degree, the valley amplitude variation degree, the peak-peak interval variation degree, the valley Gu Jian interval variation degree and the peak-valley interval variation degree, and giving out scores of signal quality; the frequency domain modes include: through amplitude-frequency characteristic analysis on the pulse signals, a score of signal quality is given by judging whether the frequency corresponding to the maximum amplitude is consistent with the pulse rate or not and calculating the ratio of the maximum peak value to the secondary peak value; the mode of combining the time domain and the frequency domain comprises the following steps: and calculating and giving a final signal quality score according to the signal quality score calculated in the time domain and the signal quality score calculated in the frequency domain and the weight corresponding to each signal quality score.
A blood pressure measurement optimization system according to an embodiment of the second aspect of the present invention includes: the pulse signal extraction module is used for extracting pulse signals in the pressure mixing curve and obtaining an envelope curve of the variation trend of the pulse signals through processing; the blood pressure calculation module is used for calculating blood pressure based on the envelope curve to obtain a blood pressure value; the signal quality evaluation module is used for analyzing the pulse signals to obtain quality evaluation coefficients of the pulse signals; a determination module that compares the quality evaluation coefficient with a set threshold value, and determines whether to use the blood pressure value calculated by the pressurization and whether to set a soft threshold value for a target pressure value; and comparing the quality evaluation coefficient with a set threshold value to determine whether to perform blood pressure calculation by a decompression method.
The blood pressure measurement optimizing system provided by the embodiment of the invention has at least the following beneficial effects: according to the embodiment of the invention, the calculation of the blood pressure and the quality evaluation of the pulse signal are completed in a relevant mode such as signal processing in the inflation stage, whether the blood pressure value is required to be calculated in a deflation measurement mode is finally determined according to the comparison between the quality evaluation factor and the threshold value, and the target pressure is set in a setting mode of the target pressure soft threshold value, so that the accurate control of the inflation target pressure is achieved, and the blood pressure measurement efficiency is improved.
According to some embodiments of the invention, the system further comprises a pressure control system for completing the setting of the target pressure value based on the calculated blood pressure value. The embodiment achieves accurate control of the inflation target pressure and improves the efficiency of blood pressure calculation.
A computer readable storage medium according to an embodiment of the third aspect of the present invention has stored thereon a computer program which, when executed by a processor, implements a method according to any of the embodiments of the first aspect of the present invention.
Since the computer-readable storage medium of the embodiment of the present invention stores thereon the computer-executable instructions for performing the blood pressure measurement optimization method according to any one of the first aspect of the present invention, all the advantageous effects of the first aspect of the present invention are achieved.
Additional aspects and advantages of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention.
Drawings
The foregoing and/or additional aspects and advantages of the invention will become apparent and may be better understood from the following description of embodiments taken in conjunction with the accompanying drawings in which:
FIG. 1 is a flow chart of a method according to an embodiment of the invention;
FIG. 2 is a schematic diagram of a pressure measurement flow chart according to an embodiment of the present invention;
FIG. 3 is a schematic diagram of a target pressure control method according to an embodiment of the present invention;
FIG. 4 is a schematic diagram of an anti-motion strategy during a depressurization measurement process according to an embodiment of the present invention;
fig. 5 is a block schematic diagram of a system according to an embodiment of the invention.
Detailed Description
Embodiments of the present invention are described in detail below, examples of which are illustrated in the accompanying drawings, wherein like or similar reference numerals refer to like or similar elements or elements having like or similar functions throughout. The embodiments described below by referring to the drawings are illustrative only and are not to be construed as limiting the invention.
In the description of the present invention, a plurality means one or more, and a plurality means two or more, and it is understood that greater than, less than, exceeding, etc. does not include the present number, and it is understood that greater than, less than, within, etc. include the present number. The description of the first and second is for the purpose of distinguishing between technical features only and should not be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated or implicitly indicating the precedence of the technical features indicated.
Referring to fig. 1, the method of the embodiment of the present invention includes the steps of: acquiring a pressure mixing curve in the inflation process, extracting pulse signals in the pressure mixing curve, and processing to obtain an envelope curve of the variation trend of the pulse signals; calculating blood pressure based on the envelope curve to obtain a blood pressure value; analyzing based on the pulse signals to obtain quality evaluation coefficients of the pulse signals; comparing the quality evaluation coefficient with a set threshold value, and determining whether to use the blood pressure value calculated by the pressurization and whether to set a soft threshold value for the target pressure value; and comparing the quality evaluation coefficient with a set threshold value, and determining whether to perform blood pressure calculation by a decompression method. In the embodiment, the calculation of the blood pressure and the quality evaluation of the pulse signal are completed in a relevant mode such as signal processing in the inflation stage, and finally, whether the blood pressure value needs to be calculated in a deflation measurement mode is determined according to the comparison between the quality evaluation factor and the threshold value.
Referring to fig. 2, in the present embodiment, the blood pressure value is calculated by a pressurization method, and during the inflation process, the pressure sensor can obtain a pressure mixing curve, and the pressure mixing curve is composed of an inflation pressure signal and a pulse signal, so in order to correspond the pulse signal to the pressure signal, we need to extract the pulse signal in the pressure mixing curve by adopting a related time domain or frequency domain mode; after the pulse signals are obtained, the time domain and the frequency domain characteristics of the pulse signals are extracted by using a time domain or frequency domain or a calculation mode combining the time domain and the frequency domain, and the method is characterized by mainly comprising amplitude-frequency characteristics of the pulse signals, such as peak amplitude, position thereof, valley amplitude, position thereof and the like. In order to obtain the envelope curve of the relevant pulse signals, linear or nonlinear interpolation modes (linear interpolation, quadratic interpolation, lagrange interpolation, cubic spline interpolation and the like) are adopted to operate the pulse signal characteristics, and finally the envelope curve of the pulse signal variation trend is obtained; and calculating the blood pressure by adopting a pressure envelope curve inflection point method and an amplitude coefficient method.
The pressure envelope curve inflection point method is a method for analyzing and calculating a blood pressure value of a pulse signal extracted from a static pressure curve, wherein a maximum peak point is marked as t, the corresponding peak amplitude is qt, the maximum value of variation is found by adopting the ratio of adjacent peak amplitudes forwards and backwards respectively, the pressure value corresponding to the maximum waveform position of forward amplitude variation is diastolic pressure, and the pressure value corresponding to the maximum waveform position of backward amplitude variation is systolic pressure. The amplitude coefficient method is a method for analyzing and calculating blood pressure for an envelope curve of a pulse signal variation trend, and because the obtained envelope curve is normalized, and because the coefficient of the general systolic pressure of a human body is 0.46-0.64 and the amplitude coefficient of the diastolic pressure is 0.43-0.73, the method respectively determines a systolic pressure coefficient S and a diastolic pressure coefficient D in the coefficient range, and then finds a point with the pressure coefficient D forward by taking the maximum value of the envelope curve as a starting point, and the pressure value corresponding to the point is the diastolic pressure. And (3) taking the maximum value of the envelope line as a starting point, finding out a point with the pressure coefficient of S backwards, and taking the pressure value corresponding to the point as the systolic pressure at the moment, thus finally completing the calculation of the blood pressure.
And analyzing the pulse characteristics and the pulse signals in a related time domain and frequency domain analysis or a time domain and frequency domain combined mode to obtain a quality evaluation coefficient (SQI) of the pulse signals, comparing the SQI with a set threshold value, and finally judging whether a blood pressure calculation result directly adopts a pressurization mode. The time domain signal quality analysis and the frequency domain signal quality analysis are described below, respectively: pulse signal features extracted from the static pressure curve are extracted including, but not limited to, peak points and locations thereof and valley points and locations thereof. Then, the obtained pulse characteristics were analyzed, and the peak amplitude variation (20 minutes), the valley amplitude variation (20 minutes), the peak-to-valley amplitude variation (10 minutes), the peak-to-peak interval variation (20 minutes), the Gu Gu interval variation (20 minutes), the peak-to-valley interval variation, and the like (10 minutes) were calculated, respectively. The amplitude variation is used for analyzing the longitudinal stability of the pulse signal. The interval variation is used for analyzing whether the pulse signal is uniform in width or not. The analysis results are all part of the morphological characteristics of the pulse signals, so that the quality of the signals can be judged based on the analysis results. And finally gives a score for the signal quality.
Signal quality frequency analysis strategy: for example, when the pulse rate obtained at this time is N, the amplitude corresponding to the frequency 1/N should be the maximum value. The judgment strategy is that if the frequency corresponding to the maximum amplitude is consistent with the pulse rate and the maximum peak value/secondary peak value is >1000, the frequency is regarded as 100 minutes at the moment; the maximum peak/sub-peak value is considered to be 60 minutes at this time if the frequency corresponding to the maximum amplitude coincides with the pulse rate and is considered to be 20 minutes at this time if neither of the above two conditions is satisfied.
The signal quality evaluation (SQI) can be performed in a time domain mode or a frequency domain mode, if the time domain mode or the frequency domain mode is adopted, the time domain mode and the frequency domain mode are adopted, and if the time domain mode and the frequency domain mode are adopted, the time domain mode and the frequency domain mode are respectively multiplied by a weight coefficient of 0.5.
In some embodiments, two set thresholds are derived by the quality assessment factor, including a first threshold and a second threshold, wherein the first threshold is less than the second threshold; when the quality evaluation coefficient is smaller than the first threshold value, setting a hard threshold value for the target pressure value; when the quality evaluation coefficient is larger than or equal to the first threshold value and smaller than or equal to the second threshold value, setting a soft threshold value for the target pressure value; when the quality evaluation coefficient is greater than the second threshold, soft threshold setting is performed on the target pressure value and the blood pressure value calculated by pressurization is output as a blood pressure measurement result.
Specifically, referring to fig. 3, by calculating SQI, we can obtain two thresholds T1, T2, T1 being 60, T2 being 80, three threshold intervals being smaller than T1, (T1, T2) and larger than T2, for evaluating the blood pressure value obtained by the pressurization mode currently, first, when the signal quality is less than T1, the blood pressure value calculated by the pressurization method is not used, and the soft threshold setting mode is not performed for the target pressure value; if the signal quality is between T1 and T2, the blood pressure value calculated by the pressurization method is not used, but the soft threshold value is set for the target pressure value; if the signal quality is greater than T2, the blood pressure result calculated in the pressurization mode is used and the target pressure soft threshold is used for setting.
If SQI > T1 at this time, movement occurs when the target pressure value is not reached and a pulse-like signal is generated, determining the signal type of the pulse-like signal according to the position where the pulse-like signal occurs at this time and the strength of the signal, and continuing the subsequent measurement step if the pulse-like signal is generated; if the pressure reaches the target pressure set in a soft threshold mode, if the pressure reaches the target pressure set in the soft threshold mode, the system can directly determine whether the blood pressure value calculated in the pressurizing mode is directly used or the pressure is measured by rotating the air, wherein the pressure is calculated by the SQI; if the target pressure set by the soft threshold has not been reached, then the inflation is continued and then a subsequent measurement operation is performed. In the embodiment, the anti-motion capability of the system is improved in the inflation process, the blood pressure value is calculated in a pressurizing mode, the position of the similar pulse wave is judged, whether the pulse wave is a real pulse wave or not is judged, and then the system performs next operation to determine whether to perform next inflation or directly perform blood pressure measurement in the deflation stage.
Referring to fig. 4, if the SQI belongs to (T1, T2) and motion occurs in a state in which the pulse is completely closed, then at this time, the system will give a motion prompt to prompt the test to stop the motion, then the system will continue to deflate, and the motion signal will be identified as an invalid signal not being used as a basis for the subsequent blood pressure calculation; if the movement occurs between the systolic pressure and the diastolic pressure, firstly, the system gives a movement prompt to prompt the tested to stop the movement, then continues to deflate and the movement signal is identified as an invalid signal and is not used as the basis for the subsequent calculation of the blood pressure; if the movement occurs between the average pressure and the diastolic pressure, firstly, the system gives a movement prompt to prompt the tested to stop the movement, then continues to deflate and the movement signal is identified as an invalid signal and is not used as the basis for the subsequent calculation of the blood pressure; if the position where the movement occurs is smaller than the diastolic pressure, the movement signal is identified as an invalid signal at the moment and is not used as the basis for the subsequent blood pressure calculation, and the blood pressure measurement is directly ended to output a blood pressure calculation result. The embodiment improves the blood pressure measurement precision in the deflation stage, and because the blood pressure value is already calculated in the inflation stage by a related signal processing mode, whether the pulse signal is generated for movement or not can be directly and reversely deduced in the subsequent deflation stage, thereby improving the blood pressure measurement precision in the deflation stage.
According to the embodiment of the invention, the target pressure is set by using the setting mode of the target pressure soft threshold value, so that the blood pressure measurement efficiency is improved. In order to ensure that the target inflation pressure can be accurately determined each time, a relevant signal processing means is adopted to extract pulse signals in the inflation stage, firstly, the quality judgment is carried out on the extracted pulse signals, then, the blood pressure value is determined through an amplitude coefficient method, a qualitative method and a pressure envelope curve inflection point method, the calculated blood pressure value is fed back to a pressure control system, and finally, the setting of the target pressure value is finished, so that the accurate control of the inflation target pressure is achieved, and the efficiency of blood pressure calculation is improved.
The invention also provides embodiments of the system corresponding to the previous embodiments. For system embodiments, reference is made to the description of method embodiments for the relevant points, since they essentially correspond to the method embodiments.
Referring to fig. 5, a blood pressure measurement optimization system according to an embodiment of the present invention includes: the pulse signal extraction module is used for extracting pulse signals in the pressure mixing curve and obtaining an envelope curve of the variation trend of the pulse signals through processing; the blood pressure calculation module is used for calculating blood pressure based on the envelope curve to obtain a blood pressure value; the signal quality evaluation module is used for analyzing based on the pulse signals to obtain quality evaluation coefficients of the pulse signals; the judging module is used for comparing the quality evaluation coefficient with a set threshold value and determining whether the blood pressure value calculated by the pressurization at this time is used and whether the target pressure value is set by a soft threshold value; and comparing the quality evaluation coefficient with a set threshold value, and determining whether to perform blood pressure calculation by a decompression method.
In some embodiments, the system of the embodiments of the present invention further comprises a pressure control system for completing the setting of the target pressure value based on the calculated blood pressure value. The embodiment achieves accurate control of the inflation target pressure and improves the efficiency of blood pressure calculation.
Although specific embodiments are described herein, those of ordinary skill in the art will recognize that many other modifications or alternative embodiments are also within the scope of the present disclosure. For example, any of the functions and/or processing capabilities described in connection with a particular device or component may be performed by any other device or component. In addition, while various exemplary implementations and architectures have been described in terms of embodiments of the present disclosure, those of ordinary skill in the art will recognize that many other modifications to the exemplary implementations and architectures described herein are also within the scope of the present disclosure.
Certain aspects of the present disclosure are described above with reference to block diagrams and flowchart illustrations of systems, methods, systems and/or computer program products according to example embodiments. It will be understood that one or more blocks of the block diagrams and flowchart illustrations, and combinations of blocks in the block diagrams and flowchart illustrations, respectively, can be implemented by executing computer-executable program instructions. Also, some of the blocks in the block diagrams and flowcharts may not need to be performed in the order shown, or may not need to be performed in their entirety, according to some embodiments. In addition, additional components and/or operations beyond those shown in blocks of the block diagrams and flowcharts may be present in some embodiments.
Accordingly, blocks of the block diagrams and flowchart illustrations support combinations of means for performing the specified functions, combinations of elements or steps for performing the specified functions and program instruction means for performing the specified functions. It will also be understood that each block of the block diagrams and flowchart illustrations, and combinations of blocks in the block diagrams and flowchart illustrations, can be implemented by special purpose hardware-based computer systems that perform the specified functions, elements or steps, or combinations of special purpose hardware and computer instructions.
Program modules, applications, etc. described herein may include one or more software components including, for example, software objects, methods, data structures, etc. Each such software component may include computer-executable instructions that, in response to execution, cause at least a portion of the functions described herein (e.g., one or more operations of the exemplary methods described herein) to be performed.
The software components may be encoded in any of a variety of programming languages. An exemplary programming language may be a low-level programming language, such as an assembly language associated with a particular hardware architecture and/or operating system platform. Software components including assembly language instructions may need to be converted into executable machine code by an assembler prior to execution by a hardware architecture and/or platform. Another exemplary programming language may be a higher level programming language that may be portable across a variety of architectures. Software components, including higher-level programming languages, may need to be converted to an intermediate representation by an interpreter or compiler before execution. Other examples of programming languages include, but are not limited to, a macro language, a shell or command language, a job control language, a scripting language, a database query or search language, or a report writing language. In one or more exemplary embodiments, a software component containing instructions of one of the programming language examples described above may be executed directly by an operating system or other software component without first converting to another form.
The software components may be stored as files or other data storage constructs. Software components having similar types or related functionality may be stored together, such as in a particular directory, folder, or library. The software components may be static (e.g., preset or fixed) or dynamic (e.g., created or modified at execution time).
The embodiments of the present invention have been described in detail with reference to the accompanying drawings, but the present invention is not limited to the above embodiments, and various changes can be made within the knowledge of one of ordinary skill in the art without departing from the spirit of the present invention.
Claims (6)
1. A blood pressure measurement optimization system, comprising:
the pulse signal extraction module is used for extracting pulse signals in the pressure mixing curve and obtaining an envelope curve of the variation trend of the pulse signals through processing;
the blood pressure calculation module is used for calculating blood pressure based on the envelope curve to obtain a blood pressure value;
the signal quality evaluation module is used for analyzing the pulse signals to obtain quality evaluation coefficients of the pulse signals;
a determination module that compares the quality evaluation coefficient with a set threshold value, and determines whether to use the blood pressure value calculated by the pressurization and whether to set a soft threshold value for a target pressure value; comparing the quality evaluation coefficient with a set threshold value, and determining whether to perform blood pressure calculation by a decompression method;
the analyzing based on the pulse signal to obtain the quality evaluation coefficient of the pulse signal includes: analyzing by a mode of combining a time domain or a frequency domain or a time domain and a frequency domain;
the time domain mode comprises the following steps:
analyzing pulse characteristics of the pulse signals, respectively calculating the peak amplitude variation degree, the valley amplitude variation degree, the peak-peak interval variation degree, the valley Gu Jian interval variation degree and the peak-valley interval variation degree, and giving out signal quality scores;
the frequency domain modes include:
through amplitude-frequency characteristic analysis on the pulse signals, a signal quality score is given by judging whether the frequency corresponding to the maximum amplitude is consistent with the pulse rate or not and calculating the ratio of the maximum peak value to the secondary peak value;
the mode of combining the time domain and the frequency domain comprises the following steps:
calculating and giving a final signal quality score according to the signal quality score calculated in the time domain, the signal quality score calculated in the frequency domain and the weight corresponding to each signal quality score;
the comparing the quality evaluation coefficient with a set threshold value, determining whether to use the blood pressure value calculated by the pressurization and whether to set a soft threshold value for a target pressure value, including:
obtaining two set thresholds through the quality evaluation coefficient, wherein the two set thresholds comprise a first threshold and a second threshold, and the first threshold is smaller than the second threshold;
when the quality evaluation coefficient is smaller than the first threshold value, the blood pressure value calculated by the pressurization is not used, and a hard threshold value is set for a target pressure value;
when the quality evaluation coefficient is larger than or equal to the first threshold value and smaller than or equal to the second threshold value, the blood pressure value calculated by the pressurization is not used, and a soft threshold value is set for a target pressure value;
when the quality evaluation coefficient is larger than the second threshold value, setting a soft threshold value for a target pressure value, and using the blood pressure value calculated by the pressurization, outputting the blood pressure value calculated by the pressurization as a blood pressure measurement result;
comparing the quality evaluation coefficient with a set threshold value to determine whether to perform blood pressure calculation by a decompression method, wherein the method comprises the following steps: and when the quality evaluation coefficient is smaller than or equal to the second threshold value, determining to perform pressure reduction method blood pressure calculation.
2. The blood pressure measurement optimization system of claim 1, wherein determining to perform a depressurization blood pressure calculation when the quality assessment coefficient is equal to or less than the second threshold value comprises: and acquiring a pulse signal in the deflation process, and analyzing and obtaining a blood pressure value measured by a decompression method based on the pulse signal.
3. The blood pressure measurement optimization system of claim 1, wherein the reduced pressure method blood pressure calculation comprises: during deflation, an anti-motion strategy is employed for motion disturbance, comprising:
if the motion signal is in a state that the pulse is completely closed, between the systolic pressure and the diastolic pressure or between the average pressure and the diastolic pressure, giving a motion prompt to prompt the tested person to stop the motion, then continuing to deflate, and identifying the motion signal as an invalid signal not serving as a basis for the subsequent blood pressure calculation;
if the position of the motion signal is smaller than the diastolic pressure, the motion signal is identified as an invalid signal and is not used as the basis for the subsequent blood pressure calculation, and the blood pressure measurement is directly ended to output a blood pressure calculation result.
4. The blood pressure measurement optimization system of claim 1, wherein the soft threshold setting comprises: and feeding the blood pressure value back to a pressure control system, and setting a target pressure value according to the blood pressure value by the pressure control system.
5. The blood pressure measurement optimization system of claim 1, wherein the system is further configured to: eliminating motion interference during inflation; the process of eliminating motion interference in the inflation process comprises the following steps:
when the target pressure value is not reached, motion occurs and a pulse-like signal is generated, and the signal type of the pulse-like signal is determined according to the position where the pulse-like signal occurs and the intensity of the pulse-like signal;
if the pulse signal is the pulse signal, continuing to carry out the subsequent measurement step;
if the pressure is the motion signal, giving out corresponding motion prompt information and sending out motion prompt, and then judging whether the pressure reaches the target pressure set in a soft threshold mode at the moment; if yes, determining a blood pressure value or a deflation measurement calculated directly by using a pressurizing mode through a range of the quality evaluation coefficient at the moment; if the target pressure set by the soft threshold has not been reached, the inflation is continued and then a subsequent measurement operation is performed.
6. The blood pressure measurement optimization system of claim 1, wherein the extracting the pulse signal in the pressure mixing curve and processing to obtain an envelope curve of the trend of the pulse signal comprises:
extracting pulse signals in the pressure mixing curve in a time domain or frequency domain mode, and extracting time domain and frequency domain characteristics of the pulse signals in a time domain or frequency domain or time domain and frequency domain combined calculation mode after obtaining the pulse signals;
and operating the characteristics of the pulse signals in a linear or nonlinear interpolation mode to finally obtain an envelope curve of the variation trend of the pulse signals.
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