CN111904403B - Blood pressure measurement system, blood pressure measurement method, computer device, and storage medium - Google Patents
Blood pressure measurement system, blood pressure measurement method, computer device, and storage medium Download PDFInfo
- Publication number
- CN111904403B CN111904403B CN201910386120.2A CN201910386120A CN111904403B CN 111904403 B CN111904403 B CN 111904403B CN 201910386120 A CN201910386120 A CN 201910386120A CN 111904403 B CN111904403 B CN 111904403B
- Authority
- CN
- China
- Prior art keywords
- blood pressure
- pressure
- pulse wave
- acceleration
- signal
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 238000000034 method Methods 0.000 title claims abstract description 101
- 238000009530 blood pressure measurement Methods 0.000 title claims abstract description 54
- 230000001133 acceleration Effects 0.000 claims abstract description 96
- 238000012545 processing Methods 0.000 claims abstract description 44
- 230000035487 diastolic blood pressure Effects 0.000 claims abstract description 38
- 230000035488 systolic blood pressure Effects 0.000 claims abstract description 38
- 230000033001 locomotion Effects 0.000 claims abstract description 31
- 238000004891 communication Methods 0.000 claims abstract description 12
- 238000001914 filtration Methods 0.000 claims description 85
- 230000003044 adaptive effect Effects 0.000 claims description 57
- 230000015654 memory Effects 0.000 claims description 15
- 238000004590 computer program Methods 0.000 claims description 8
- 230000006870 function Effects 0.000 claims description 8
- 101150029607 SS18L1 gene Proteins 0.000 claims description 7
- 238000006243 chemical reaction Methods 0.000 claims description 6
- 230000000630 rising effect Effects 0.000 claims description 3
- 230000036772 blood pressure Effects 0.000 abstract description 50
- 238000012544 monitoring process Methods 0.000 abstract description 15
- 238000005259 measurement Methods 0.000 abstract description 13
- 238000012937 correction Methods 0.000 abstract 1
- 230000004872 arterial blood pressure Effects 0.000 description 17
- 230000008859 change Effects 0.000 description 17
- 230000007423 decrease Effects 0.000 description 17
- 230000008569 process Effects 0.000 description 17
- 208000024172 Cardiovascular disease Diseases 0.000 description 7
- 230000000694 effects Effects 0.000 description 7
- 210000004204 blood vessel Anatomy 0.000 description 6
- 230000000747 cardiac effect Effects 0.000 description 6
- 238000010586 diagram Methods 0.000 description 6
- 230000002861 ventricular Effects 0.000 description 6
- 238000005516 engineering process Methods 0.000 description 5
- 238000000691 measurement method Methods 0.000 description 5
- 230000007547 defect Effects 0.000 description 4
- 230000007613 environmental effect Effects 0.000 description 4
- 230000009084 cardiovascular function Effects 0.000 description 3
- 230000001276 controlling effect Effects 0.000 description 3
- 238000012806 monitoring device Methods 0.000 description 3
- 230000010355 oscillation Effects 0.000 description 3
- 206010017472 Fumbling Diseases 0.000 description 2
- 238000004458 analytical method Methods 0.000 description 2
- 238000001514 detection method Methods 0.000 description 2
- 239000011159 matrix material Substances 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 230000003287 optical effect Effects 0.000 description 2
- 230000001105 regulatory effect Effects 0.000 description 2
- 238000011160 research Methods 0.000 description 2
- 230000009471 action Effects 0.000 description 1
- 238000013459 approach Methods 0.000 description 1
- 230000033228 biological regulation Effects 0.000 description 1
- 239000008280 blood Substances 0.000 description 1
- 210000004369 blood Anatomy 0.000 description 1
- 239000003990 capacitor Substances 0.000 description 1
- 230000001364 causal effect Effects 0.000 description 1
- 239000002131 composite material Substances 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 238000012850 discrimination method Methods 0.000 description 1
- 239000006185 dispersion Substances 0.000 description 1
- 238000006073 displacement reaction Methods 0.000 description 1
- 239000003292 glue Substances 0.000 description 1
- PCHJSUWPFVWCPO-UHFFFAOYSA-N gold Chemical compound [Au] PCHJSUWPFVWCPO-UHFFFAOYSA-N 0.000 description 1
- 230000036541 health Effects 0.000 description 1
- 230000005764 inhibitory process Effects 0.000 description 1
- 238000009434 installation Methods 0.000 description 1
- 238000004519 manufacturing process Methods 0.000 description 1
- 230000035772 mutation Effects 0.000 description 1
- 238000010606 normalization Methods 0.000 description 1
- 230000002093 peripheral effect Effects 0.000 description 1
- 230000002265 prevention Effects 0.000 description 1
- 230000009467 reduction Effects 0.000 description 1
- 230000004044 response Effects 0.000 description 1
- 230000035945 sensitivity Effects 0.000 description 1
- 238000012549 training Methods 0.000 description 1
- 238000012546 transfer Methods 0.000 description 1
- 238000011269 treatment regimen Methods 0.000 description 1
Classifications
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/02—Detecting, measuring or recording for evaluating the cardiovascular system, e.g. pulse, heart rate, blood pressure or blood flow
- A61B5/021—Measuring pressure in heart or blood vessels
- A61B5/02108—Measuring pressure in heart or blood vessels from analysis of pulse wave characteristics
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/02—Detecting, measuring or recording for evaluating the cardiovascular system, e.g. pulse, heart rate, blood pressure or blood flow
- A61B5/021—Measuring pressure in heart or blood vessels
- A61B5/02108—Measuring pressure in heart or blood vessels from analysis of pulse wave characteristics
- A61B5/02116—Measuring pressure in heart or blood vessels from analysis of pulse wave characteristics of pulse wave amplitude
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/02—Detecting, measuring or recording for evaluating the cardiovascular system, e.g. pulse, heart rate, blood pressure or blood flow
- A61B5/021—Measuring pressure in heart or blood vessels
- A61B5/022—Measuring pressure in heart or blood vessels by applying pressure to close blood vessels, e.g. against the skin; Ophthalmodynamometers
- A61B5/0225—Measuring pressure in heart or blood vessels by applying pressure to close blood vessels, e.g. against the skin; Ophthalmodynamometers the pressure being controlled by electric signals, e.g. derived from Korotkoff sounds
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/72—Signal processing specially adapted for physiological signals or for diagnostic purposes
- A61B5/7235—Details of waveform analysis
- A61B5/725—Details of waveform analysis using specific filters therefor, e.g. Kalman or adaptive filters
Landscapes
- Health & Medical Sciences (AREA)
- Life Sciences & Earth Sciences (AREA)
- Cardiology (AREA)
- Engineering & Computer Science (AREA)
- Public Health (AREA)
- Medical Informatics (AREA)
- Vascular Medicine (AREA)
- Physics & Mathematics (AREA)
- Physiology (AREA)
- Biophysics (AREA)
- Pathology (AREA)
- Biomedical Technology (AREA)
- Heart & Thoracic Surgery (AREA)
- Veterinary Medicine (AREA)
- Molecular Biology (AREA)
- Surgery (AREA)
- Animal Behavior & Ethology (AREA)
- General Health & Medical Sciences (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Psychiatry (AREA)
- Ophthalmology & Optometry (AREA)
- Signal Processing (AREA)
- Artificial Intelligence (AREA)
- Measuring Pulse, Heart Rate, Blood Pressure Or Blood Flow (AREA)
Abstract
The invention provides a blood pressure measuring system, a blood pressure measuring method, a computer device and a storage medium, comprising: the kit is provided with an air bag and is used for being fixed at a part to be measured; the gas circuit module is connected with the sleeve; for inflating and deflating the balloon; the pressure signal acquisition module is connected with the sleeve and is used for acquiring pressure signals in the sleeve; the acceleration acquisition module is used for outputting corresponding acceleration digital signals; the processing module is in communication connection with the pressure signal acquisition module, the gas circuit module and the acceleration acquisition module, and is used for obtaining a first envelope line and a second envelope line and obtaining systolic pressure and diastolic pressure according to the obtained correction peak value sequence. The method is used for solving the problem that in the prior art, on wearable blood pressure monitoring equipment such as a dynamic blood pressure measuring system and the like, the movement interference especially affects the measurement accuracy, so that the anti-movement interference capability is greatly improved, and the blood pressure measurement accuracy is improved.
Description
Technical Field
The present invention relates to the field of electronic information and biomedicine, and more particularly, to a blood pressure measurement system, a blood pressure measurement method, a computer device, and a storage medium.
Background
With the development of society, cardiovascular diseases have increasingly affected the health of many people. Therefore, the method has important positive significance for controlling and managing the cardiovascular diseases. The treatment strategy of cardiovascular diseases is mainly prevention, which requires that the high risk group of cardiovascular diseases pay attention to the cardiovascular function state of the people at any time. Blood pressure is the pressure of blood flowing in a blood vessel of a human body per unit area against the wall of the blood vessel flowing through the blood pressure. The blood pressure of the human body is classified into systolic pressure, mean arterial pressure and diastolic pressure. During a cardiac cycle, ventricular systole causes the main arterial pressure to rise sharply and to reach a maximum at the mid-systole, where the arterial pressure value is called systolic pressure; the ventricular diastole can lead to the reduction of the main arterial blood pressure and reach the minimum value at the end diastole, and the arterial blood pressure value at the moment is the diastolic blood pressure; the mean arterial pressure is then the mean value of the arterial pressure during one cardiac cycle. Blood pressure is an important physiological parameter of a human body and is one of important indexes for reflecting whether the cardiovascular function of the human body is good. There is a close causal relationship between the blood pressure and the risk of cardiovascular disease onset and death. Therefore, the blood pressure parameters of the human body are monitored in real time in daily life, so that the cardiovascular function state can be known, the risk of suffering from the cardiovascular disease can be reduced, and the effects of preventing and controlling the cardiovascular disease can be achieved.
Blood pressure measurement methods are mainly divided into two major categories, namely invasive measurement methods and noninvasive measurement methods. Among them, the invasive measurement method is to insert a catheter connected with a pressure sensor directly into an arterial vessel or heart of a human body. Although the method can accurately measure the blood pressure value, the method needs to be operated by professional medical staff at a designated place, has a certain damage to human bodies, is generally used in an intensive care unit, and is not suitable for daily monitoring in families. The noninvasive blood pressure measurement technology is widely used for daily home monitoring due to simple operation and noninvasive property. At present, most of the existing products in the market are developed based on a non-invasive blood pressure measurement technology, and three methods for mainly applying the non-invasive blood pressure measurement technology to the market products are as follows: korotkoff sounds, constant volume, and oscillography. The Korotkoff sound method is known as a gold standard for noninvasive blood pressure measurement, but is often used in places such as hospital outpatient service and the like and is not suitable for daily monitoring at home because an operator of the Korotkoff sound method needs professional training and is easily influenced by subjective factors of the operator and noise of surrounding environment in the measurement process.
Non-invasive blood pressure measurements have evolved to date with many measurement techniques. The noninvasive blood pressure monitoring operation is simple, convenient and quick, so that the noninvasive blood pressure monitoring device is widely applied clinically, and the working efficiency of medical workers is greatly improved. Oscillometric methods, also known as oscillation methods, developed in the last 70 th century, are one of the most widely used methods in electronic blood pressure meters. The method is similar to the Korotkoff sound method in measurement process, but the blood pressure is not judged by the existence of Korotkoff sound. In the oscillometric measurement process, the pressure in the cuff is pressurized to the specified pressure, the pulse wave amplitude value is detected, if the amplitude value is still larger, the pressurization is continued until the pulse wave amplitude value reaches the minimum value, and at the moment, the arterial blood vessel is in a closed state; then, the linear deflation is started, the pulse wave amplitude value is detected in the deflation process, the pulse wave amplitude value is slowly increased along with the gradual decrease of the pressure in the cuff, and when the pressure is reduced to the vicinity of the systolic pressure Ps, the pulse wave amplitude value is obviously increased. When the pulse wave amplitude value reaches the maximum, the corresponding cuff pressure is the average pressure Pm, and the blood vessel wall is in a load-removing state; as the pressure in the cuff continues to decrease, the pulse wave amplitude begins to decrease, and when the pressure in the cuff decreases to about the diastolic pressure Pd, the pulse wave amplitude decreases significantly, and then slowly decreases as the pressure decreases gradually. The oscillometric method is adopted to measure, so that the influence of subjective factors of operators can be eliminated, the interference of environmental noise can be avoided, and the accuracy is improved; secondly, in the measuring process, not only the systolic pressure and the diastolic pressure can be obtained, but also the accurate average pressure can be obtained; finally, oscillometric measurements facilitate computer processing, and facilitate storage and analysis of data. Of course, the oscillometric method also has difficulties to overcome. Firstly, the signals measured by the oscillometric method are oscillation wave signals superposed on the basis of blood pressure signals, so that the frequency components of the blood pressure change are weakened, the capability of the blood pressure change is slightly insufficient, secondly, the oscillometric method is extremely easy to be influenced by the motion interference of a human body, and the motion interference resistance is required to be improved. The judging method for measuring the blood pressure based on the oscillography is a lot, and can be mainly divided into a waveform characteristic method and an amplitude coefficient method at present.
The waveform characteristic method starts from the envelope curve of the pulse wave sequence, and determines the systolic pressure and the diastolic pressure by analyzing the characteristics near the systolic pressure and the diastolic pressure in the envelope curve. Typical wave characteristics methods are as follows: (1) mutation Point method: the abrupt change point method considers that in the process of gradually reducing the pressure in the cuff, the pulse wave amplitude has a significant increase position and a significant decrease position, which correspond to points where the systolic pressure and the diastolic pressure respectively correspond to the pulse wave amplitude. The discrimination criterion determines the variation value of the amplitude of the adjacent pulse wave through a differential algorithm, and the maximum point of the difference value is the abrupt point. (2) envelope curve inflection point discrimination method: jiang Guotai and zhai teng men put forward an idealized upper arm moving tissue transfer model from the point of view of mechanics principle, and prove that the systolic pressure and the diastolic pressure correspond to inflection points of pulse wave envelope curves. While this approach is theoretically possible, it can be very difficult to find the inflection point of the envelope when designing the instrument. Because the algorithm for fitting the envelope is different, the location of the inflection point will also change.
The amplitude coefficient method is also called normalization method, i.e. the ratio of the pulse wave amplitude value to the maximum pulse wave amplitude value is used as an important parameter for determining the systolic pressure and the diastolic pressure. The key of the method is to determine the proportional coefficient corresponding to the systolic pressure and the diastolic pressure, and estimate the proportional coefficient through a large amount of experimental data statistics. The ratio between the pulse wave amplitude corresponding to the systolic or diastolic pressure and the maximum pulse wave amplitude is about 75% -80%. The proportional coefficient method has a certain effect on specific crowds, and an empirical formula obtained through a large amount of experimental statistics is adopted, so that the method has no unified standard. However, for individual differences, the amplitude coefficient method cannot be well adapted, and the accuracy is lowered.
For the respective defects of the waveform characteristic method and the amplitude coefficient method, many scholars propose an improved method based on the defects. The coefficient differential ratio method does not take the simple adjacent pulse wave difference value as the basis when finding the abrupt change point, but rather uses the relative change value of the pulse wave amplitude, so that the influence caused by the larger difference value due to the large pulse wave amplitude value near the average pressure can be avoided. However, in this way, when the pulse wave amplitude value is small, the relative change value is large, and the result is that the systolic blood pressure becomes higher and the diastolic blood pressure becomes lower. Aiming at the problem, the reference amplitude coefficient method of the coefficient differential ratio method is used for searching the pulse wave with larger relative change value in a certain range, so that the accuracy is effectively improved. Although the improved coefficient differential ratio method improves the accuracy of a simple abrupt-change point method and an amplitude coefficient method to a certain extent, the method still has certain defects because the measured pulse wave amplitude and the true value possibly have errors and singular points possibly exist in the pulse wave sequence due to the existence of various interference factors.
A blood pressure judging method based on Gaussian fitting. Firstly, extracting a pulse wave amplitude value, then, carrying out Gaussian fitting on a wave crest sequence to obtain an envelope curve, and then, utilizing an empirical formula provided by the envelope curve to obtain a blood pressure value. According to the method, the Gaussian fitting envelope curve is adopted, so that errors caused by wave crest dispersion can be avoided, but the envelope curve of the pulse wave crest sequence is not a symmetrical graph, so that the Gaussian bell curve is used for fitting, and errors are introduced.
Oscillography is the most widely used non-invasive blood pressure measurement technique in current market products. The oscillography effectively eliminates the influence of subjective factors of operators and the interference of environmental noise, but is easy to be interfered by the arm movement of a testee, especially on wearable blood pressure monitoring equipment such as a dynamic blood pressure measuring system, the movement interference especially affects the measurement accuracy. Although the anti-motion interference technology of the wearable physiological parameter monitoring equipment has a certain foundation, the anti-motion interference research on the blood pressure measurement process is still weak, and the wearable physiological parameter monitoring equipment is still in a fumbling stage.
Disclosure of Invention
In view of the above-mentioned drawbacks of the prior art, an object of the present invention is to provide a blood pressure measurement system, a blood pressure measurement method, a computer device and a storage medium, which are used for solving the problem that in the prior art, in a wearable blood pressure monitoring device such as a dynamic blood pressure measurement system, the accuracy of the measurement is not high due to motion interference.
To achieve the above and other related objects, the present invention provides a blood pressure measurement system comprising: the kit is provided with an air bag and is used for being fixed at a part to be measured; the gas circuit module is connected with the sleeve; for inflating and deflating the balloon; the pressure signal acquisition module is connected with the sleeve and is used for acquiring pressure signals in the sleeve; the acceleration acquisition module is used for acquiring acceleration data of the movement of the part to be detected in real time and outputting corresponding acceleration digital signals; the processing module is in communication connection with the pressure signal acquisition module, the gas circuit module and the acceleration acquisition module, and is used for filtering the pressure signal by using the acceleration digital signal as an adaptive filtering reference signal through an adaptive filtering method to obtain a filtering processing pressure signal, dividing the peak value sequence into two parts according to the maximum peak value point reached by the peak value sequence of the detected filtering processing pressure signal, respectively obtaining a first envelope line for judging the systolic pressure and a second envelope line for judging the diastolic pressure through Gaussian fitting, further obtaining a corrected peak value sequence, and obtaining the systolic pressure and the diastolic pressure according to the corrected peak value sequence.
In an embodiment of the present invention, the adaptive filtering method uses an NLMS adaptive filtering algorithm for filtering.
In one embodiment of the present invention, the NLMS adaptive filtering algorithm comprises:
The following steps are adopted at the time n:
e(n)＝d(n)-y(n)；
y(n)＝WT(n)X(n)；
Where e (n) is the error signal, d (n) is the desired signal, and y (n) is the desired output value; μ is a step size factor; w (n) is the filter coefficient vector estimation at time n; w (n+1) is an updated filter coefficient vector estimation value P (n) =x T (n) X (n), which is a power estimation value of the input signal; x (N) = [ X (N), X (N-1), X (N-n+1) ] is an input acceleration signal at time N; alpha is a positive constant.
In an embodiment of the present invention, further includes: the safety module is coupled with the gas circuit module and the pressure signal acquisition module and is used for forcedly deflating when the pressure signal is detected to be too high; or a communication module coupled to the processing module for transmitting the blood pressure value to an external system.
To achieve the above and other related objects, the present invention provides a blood pressure measuring method applied to an adaptive filtering blood pressure measuring system, the system comprising: the kit is provided with an air bag and is used for being fixed at a part to be measured; the gas circuit module is connected with the sleeve; for inflating and deflating the balloon; the pressure signal acquisition module is connected with the sleeve and is used for acquiring pressure signals in the sleeve; the acceleration acquisition module is used for acquiring acceleration data of the movement of the part to be detected in real time and outputting corresponding acceleration digital signals; the method comprises the following steps: filtering the pressure signal by using the acceleration digital signal as an adaptive filtering reference signal through an adaptive filtering method to obtain a filtering processing pressure signal; dividing the peak value sequence into two parts according to the maximum peak value reached by the detected peak value sequence of the filtering processing pressure signal, respectively obtaining a first envelope curve for judging the systolic pressure and a second envelope curve for judging the diastolic pressure through Gaussian fitting, further obtaining a corrected peak value sequence, and obtaining the systolic pressure and the diastolic pressure according to the corrected peak value sequence.
In an embodiment of the present invention, the adaptive filtering method uses an NLMS adaptive filtering algorithm for filtering.
In one embodiment of the present invention, the NLMS adaptive filtering algorithm comprises:
The following steps are adopted at the time n:
e(n)＝d(n)-y(n)；
y(n)＝WT(n)X(n)；
Where e (n) is the error signal, d (n) is the desired signal, and y (n) is the desired output value; μ is a step size factor; w (n) is the filter coefficient vector estimation at time n; w (n+1) is an updated filter coefficient vector estimation value P (n) =x T (n) X (n), which is a power estimation value of the input signal; x (N) = [ X (N), X (N-1), X (N-n+1) ] is an input acceleration signal at time N; alpha is a positive constant.
To achieve the above and other related objects, the present invention provides a computer apparatus comprising: one or more memories for storing computer programs; one or more processors for performing the blood pressure measurement method.
To achieve the above and other related objects, the present invention provides a computer-readable storage medium having stored thereon a computer program which, when run, implements the blood pressure measurement method.
As described above, the blood pressure measurement system, the blood pressure measurement method, the computer device, and the storage medium of the present application have the following advantageous effects: the application solves the problem that in the prior art, on wearable blood pressure monitoring equipment such as a dynamic blood pressure measuring system and the like, the accuracy of the measurement is affected by motion interference, so that the accuracy of blood pressure measurement results is low.
Drawings
Fig. 1 is a schematic diagram of a blood pressure measurement system according to an embodiment of the application. .
Fig. 2 is a schematic diagram of a blood pressure measurement system according to an embodiment of the application.
Fig. 3 is a flowchart of a blood pressure measurement method according to an embodiment of the application.
Fig. 4 is a schematic structural diagram of a computer device according to an embodiment of the application.
Description of element reference numerals
10. Blood pressure measuring system
11. Kit of parts
12. Gas circuit module
13. Pressure signal acquisition module
14. Acceleration acquisition module
15. Processing module
20. Blood pressure measuring system
21. Kit of parts
22. Gas circuit module
23. Pressure signal acquisition module
24. Acceleration acquisition module
25. Processing module
26. Security module
27. Communication module
40. Computer device
41. Memory device
42. Processor and method for controlling the same
S301 to S302 steps
Detailed Description
Other advantages and effects of the present invention will become apparent to those skilled in the art from the following disclosure, which describes the embodiments of the present invention with reference to specific examples. The invention may be practiced or carried out in other embodiments that depart from the specific details, and the details of the present description may be modified or varied from the spirit and scope of the present invention. It should be noted that the following embodiments and features in the embodiments may be combined with each other without conflict.
In the following description, reference is made to the accompanying drawings, which illustrate several embodiments of the application. It is to be understood that other embodiments may be utilized and that mechanical, structural, electrical, and operational changes may be made without departing from the spirit and scope of the present application. The following detailed description is not to be taken in a limiting sense, and the scope of embodiments of the present application is defined only by the claims of the issued patent. The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the application. Spatially relative terms, such as "upper," "lower," "left," "right," "lower," "below," "lower," "above," "upper," and the like, may be used herein to facilitate a description of one element or feature as illustrated in the figures relative to another element or feature.
Throughout the specification, when a portion is said to be "coupled" to another portion, this includes not only the case of "direct connection" but also the case of "indirect connection" with other elements interposed therebetween. In addition, when a certain component is said to be "included" in a certain section, unless otherwise stated, other components are not excluded, but it is meant that other components may be included.
The first, second, and third terms are used herein to describe various portions, components, regions, layers and/or sections, but are not limited thereto. These terms are only used to distinguish one portion, component, region, layer or section from another portion, component, region, layer or section. Thus, a first portion, component, region, layer or section discussed below could be termed a second portion, component, region, layer or section without departing from the scope of the present application.
Furthermore, as used herein, the singular forms "a", "an" and "the" are intended to include the plural forms as well, unless the context indicates otherwise. It will be further understood that the terms "comprises," "comprising," "includes," and/or "including" specify the presence of stated features, operations, elements, components, items, categories, and/or groups, but do not preclude the presence, presence or addition of one or more other features, operations, elements, components, items, categories, and/or groups. The terms "or" and/or "as used herein are to be construed as inclusive, or meaning any one or any combination. Thus, "A, B or C" or "A, B and/or C" means "any of the following: a, A is as follows; b, a step of preparing a composite material; c, performing operation; a and B; a and C; b and C; A. b and C). An exception to this definition will occur only when a combination of elements, functions or operations are in some way inherently mutually exclusive.
Non-invasive blood pressure measurements have evolved to date with many measurement techniques. The noninvasive blood pressure monitoring operation is simple, convenient and quick, so that the noninvasive blood pressure monitoring device is widely applied clinically, and the working efficiency of medical workers is greatly improved. Oscillography, also known as oscillation, is the most widely used non-invasive blood pressure measurement technique in current market products. In the oscillometric measurement process, the pressure in the cuff is pressurized to the specified pressure, the pulse wave amplitude value is detected, if the amplitude value is still larger, the pressurization is continued until the pulse wave amplitude value reaches the minimum value, and at the moment, the arterial blood vessel is in a closed state; then, the linear deflation is started, the pulse wave amplitude value is detected in the deflation process, the pulse wave amplitude value is slowly increased along with the gradual decrease of the pressure in the cuff, and when the pressure is reduced to the vicinity of the systolic pressure Ps, the pulse wave amplitude value is obviously increased. When the pulse wave amplitude value reaches the maximum, the corresponding cuff pressure is the average pressure Pm, and the blood vessel wall is in a load-removing state; as the pressure in the cuff continues to decrease, the pulse wave amplitude begins to decrease, and when the pressure in the cuff decreases to about the diastolic pressure Pd, the pulse wave amplitude decreases significantly, and then slowly decreases as the pressure decreases gradually. The oscillometric method is adopted to measure, so that the influence of subjective factors of operators can be eliminated, the interference of environmental noise can be avoided, and the accuracy is improved; secondly, in the measuring process, not only the systolic pressure and the diastolic pressure can be obtained, but also the accurate average pressure can be obtained; finally, oscillometric measurements facilitate computer processing, and facilitate storage and analysis of data. Of course, the oscillometric method also has difficulties to overcome.
However, the oscillography effectively eliminates the influence of subjective factors of operators and the interference of environmental noise, but is easy to be interfered by the arm movement of a testee, especially on wearable blood pressure monitoring equipment such as a dynamic blood pressure measuring system, the movement interference especially affects the measurement accuracy. Although the anti-motion interference technology of the wearable physiological parameter monitoring equipment has a certain foundation, the anti-motion interference research on the blood pressure measurement process is still weak, and the wearable physiological parameter monitoring equipment is still in a fumbling stage.
Therefore, the application improves the blood pressure measuring system, which is used for solving the problem that the accuracy of a blood pressure measuring result is not high due to the fact that the accuracy of the blood pressure measuring result is particularly influenced by motion interference on wearable blood pressure monitoring equipment such as a dynamic blood pressure measuring system in the prior art, so that the anti-motion interference capability is greatly improved, and the blood pressure measuring accuracy is improved.
The system comprises: comprising the following steps: the kit is provided with an air bag and is used for being fixed at a part to be measured; the gas circuit module is connected with the sleeve; for inflating and deflating the balloon; the pressure signal acquisition module is connected with the sleeve and is used for acquiring pressure signals in the sleeve; the acceleration acquisition module is used for acquiring acceleration data of the movement of the part to be detected in real time and outputting corresponding acceleration digital signals; the processing module is in communication connection with the pressure signal acquisition module, the gas circuit module and the acceleration acquisition module, and is used for filtering the pressure signal by using the acceleration digital signal as an adaptive filtering reference signal through an adaptive filtering method to obtain a filtering processing pressure signal, dividing the peak value sequence into two parts according to the maximum peak value point reached by the peak value sequence of the detected filtering processing pressure signal, respectively obtaining a first envelope line for judging the systolic pressure and a second envelope line for judging the diastolic pressure through Gaussian fitting, further obtaining a corrected peak value sequence, and obtaining the systolic pressure and the diastolic pressure according to the corrected peak value sequence.
An embodiment of the present application will be described in detail below with reference to fig. 1 so that those skilled in the art to which the present application pertains can easily implement the present application. This application may be embodied in many different forms and is not limited to the embodiments described herein.
Fig. 1 is a schematic diagram of a blood pressure measurement system 10 according to an embodiment of the present application.
Comprising the following steps: a kit 11 having an air bag for fixing to a site to be measured; the kit 11 includes a balloon having a space for storing gas or for inflation and deflation; the external member can be overlapped at the position of awaiting measuring in order to be used for fixedly, the external member can come the free regulation elasticity according to the size and the shape of position of awaiting measuring and can enclose into the circle form in order to guarantee relatively confined fixed range to guarantee that the gasbag gives a pressure of position of awaiting measuring in external member one side. The position to be measured may be any position where blood pressure can be measured, such as an arm area or a leg area.
The air path module 12 is connected with the sleeve 11 and is used for inflating and deflating the air bag; the air circuit module 12 includes means for either inflating or deflating the air cells, preferably by using an air pump that removes air from or adds air to an enclosed space and an air valve that controls the flow of air into or out of the enclosed space. It should be noted that the connection of the gas circuit module 12 to the sleeve 11 refers to a process of connecting two separate sections or parts into a complex part or component by using a fastener such as a screw, a bolt, a rivet, or glue, and is not limited to one of these methods.
The pressure signal acquisition module 13 is connected with the sleeve 11 and is used for acquiring pressure signals in the sleeve; specifically, the pressure signal collecting module 13 may sense, collect or process a corresponding pressure signal, the pressure signal collecting module 13 senses a pressure signal from the external member 11 and collects or processes the pressure signal, preferably, the pressure signal collecting module 13 includes a pressure sensor, and the pressure sensor may sense a small change of pressure in the external member; for example, the pressure sensor is an MPS-3117-006GC pressure sensor, the measuring range is 0-300mmHg, the pressure sensor is specially designed for measuring blood pressure, and the pressure sensor is powered by a constant current source, has a superior temperature coefficient, and has good performance in aspects of stability, drift inhibition and the like in blood pressure measurement application.
The acceleration acquisition module 14 is used for acquiring acceleration data of the movement of the part to be detected in real time and outputting corresponding acceleration digital signals; specifically, the acceleration acquisition module 14 receives the motion signal of the part to be detected and senses the motion signal to obtain corresponding acceleration data, and then correspondingly converts and amplifies the acceleration data to obtain corresponding acceleration digital signals and outputs the corresponding acceleration digital signals; preferably, the acceleration acquisition module 14 has a component for realizing one or more functions of a sensing element, a conversion element, an amplifying circuit and a digital conversion element, when the sensing element is deformed by the movement of the part to be detected, the conversion element measures the deformation of the sensing element to obtain acceleration data, then converts the acceleration data into a measurable acceleration electric signal, the acceleration electric signal is amplified by the amplifying circuit, the signal-to-noise ratio is improved, and finally, the acceleration electric signal is digitally converted into an acceleration digital signal for output, and the acceleration acquisition module can use an acceleration sensor to complete the functions.
The acceleration sensor can be applied to a piezoelectric acceleration motion sensor, a piezoresistive acceleration sensor, a capacitive acceleration sensor and the like. The piezoelectric acceleration motion sensor directly converts mechanical energy into electric energy by utilizing the piezoelectric effect of a piezoelectric element. The piezoelectric acceleration motion sensor has the characteristics of wide frequency range, large dynamic range, small external interference and the like, but cannot measure signals with zero frequency. The basic principle of the piezoresistive acceleration sensor is that the change of acceleration is converted into the change of resistance value, and then the change of the acceleration is converted into the corresponding voltage change piezoresistive sensor through constant current, and the piezoresistive acceleration sensor has the advantages of good linearity, simple peripheral circuit, high precision, small size, easiness in installation and the like. The basic principle of the capacitive acceleration sensor is that one electrode of a capacitor is fixed, then an elastic diaphragm is used as the other electrode which can be changed, the elastic diaphragm can displace under the action of external force, so that the capacitance is changed, and the acceleration is measured by measuring the change of the capacitance. The capacitive acceleration sensor has the advantages of small volume, simple structure, few factors influencing stability, no internal and external friction and contact stress errors, low inherent sensitivity to temperature change, high precision, good dynamic response and high resolution, can realize non-contact measurement, and is widely applied to the low-frequency detection fields of pressure, displacement, acceleration, vibration and the like. In addition, the chip of the capacitive acceleration motion sensor is small in size, and can output direct digital quantity or analog quantity, so that the capacitive acceleration motion sensor is very convenient to use in combination with a singlechip or other microprocessors. It should be noted that the types of acceleration sensors used in the present application are not limited to piezoelectric acceleration motion sensors, piezoresistive acceleration sensors, and capacitive acceleration sensors, and acceleration sensors of different types may be used, which is not limited in the present application. For example, the acceleration acquisition module 14 includes an LIS3DH three-axis acceleration sensor that can digitally output X, Y, Z three-directional acceleration data.
The processing module 15 is in communication connection with the pressure signal acquisition module 13 and the gas circuit module 12 and is in communication connection with the acceleration acquisition module 14, the processing module 15 receives the pressure signal from the pressure signal acquisition module 13, wherein the pressure signal comprises a motion interference signal, and the pressure signal is filtered according to an adaptive filtering method by receiving the acceleration digital signal from the acceleration acquisition module 14 as an adaptive filtering reference signal to obtain a filtering processing pressure signal;
dividing the peak sequence into two parts by taking the maximum peak point of the peak sequence as a demarcation point according to the peak sequence of the wave detected by the obtained filtering processing signal, carrying out Gaussian fitting on one part to obtain a first envelope, judging the systolic pressure according to the first envelope, carrying out Gaussian fitting on the other part to obtain a second envelope, and judging the diastolic pressure according to the second envelope; wherein, in a cardiac cycle, ventricular systole causes the main arterial pressure to rise sharply and reach a maximum in the middle of the systole, the arterial pressure value at which is called systolic pressure; and ventricular diastole causes the aortic blood pressure to drop and reach a minimum at end diastole, where the arterial blood pressure value is the diastolic pressure. The mean arterial pressure is then the mean value of the arterial pressure during one cardiac cycle. The corresponding searching range of the characteristic points is determined according to the average pressure, namely, the fitting curve is brought into the previously stored time to obtain a new peak sequence, namely, a corrected peak sequence, and then a significant increase position and a significant decrease position are provided according to the pulse wave amplitude, and the systolic pressure and the diastolic pressure are respectively calculated corresponding to the points of the systolic pressure and the diastolic pressure corresponding to the sudden change of the pulse wave amplitude, so that the blood pressure value after interference filtering is obtained.
Specifically, the determination of the diastolic and systolic pressures is made by observing typical waveforms, and the pulse wave is first detected as a rising edge of a whistle, so the start and end points of the pulse wave are determined by detecting the rising edge. The maximum value between the start point and the end point corresponds to the peak of the current pulse wave. Since interference is easily introduced during the measurement, the pulse wave sequence obtained by detection cannot be immediately used for curve fitting, and some singular pulse waves need to be removed through proper processing. That is, by comparing the magnitude of the amplitude and the pulse wave interval, the singular pulse wave is removed. Firstly, traversing a pulse wave sequence to obtain the intervals between all adjacent pulse waves, wherein the intervals are concentrated and gathered at a point which is far away from the point, and the point is regarded as an interference point. If the amplitude of the current pulse wave i is less than 80% or more than 120% of the average value of the amplitude of the front and rear pulse waves, replacing the current pulse wave amplitude with the average value; if the pulse wave i is closer to the pulse wave i-1 and the pulse wave i is closer to the pulse wave i+1, this point is an interference point and should be removed. And then selecting a proper fitting curve to fit the envelope curve, and respectively performing Gaussian curve fitting on pulse wave sequences at two sides of the maximum pulse wave amplitude. The pulse wave peak value sequence is divided into two parts by taking the maximum peak point as a boundary, the front part is singly subjected to Gaussian fitting to obtain an envelope 1 for obtaining the systolic pressure, the rear part is singly subjected to Gaussian fitting to obtain an envelope 2 for obtaining the diastolic pressure, and then the blood pressure value is obtained. The method not only solves the problem of poor individual adaptability, but also overcomes the influence of interference signals in the process of searching the characteristic points of the waveform characteristic method by using curve fitting, and improves the accuracy of searching the characteristic points, thereby improving the accuracy of blood pressure measurement.
Optionally, the adaptive filtering method utilizes an NLMS adaptive filtering algorithm for filtering; specifically, the processing module 15 receives the pressure signal from the pressure signal acquisition module 13, where the pressure signal includes a motion interference signal, and filters the pressure signal according to an NLMS adaptive filtering algorithm by receiving the acceleration digital signal from the acceleration acquisition module 14 as an adaptive filtering reference signal to obtain a filtered pressure signal. The NLMS adaptive filtering algorithm is implemented by an adaptive filter.
In order to achieve the target filtering effect, the adaptive filter is designed according to the currently common adaptive filtering algorithm, such as the least Squares error algorithm (LEAST MEAN square, LMS), the normalized mean square error algorithm, the recursive least Squares algorithm (Recursive Least Squares, RLS), and the adaptive filtering of the frequency domain, and is typically the LMS and RLS algorithms. However, in most cases where adaptive filter processing is required, we cannot know the characteristics of the input signal, and the input signal changes over time, and it is impossible to directly measure the target filtering.
For this purpose, an improved algorithm NLMS (Normalized LMS, NLMS) algorithm is adopted, the core idea of which is to adjust the compensation factor μ according to the input n moment of the adaptive filter, n being proportional to the steady state error, μ being inversely proportional to the steady state error, and to reduce the steady state error by adjusting μ as the input n increases continuously.
Alternatively, we use an adaptive filter to filter using NLMS adaptive filtering algorithms. The NLMS adaptive filtering algorithm comprises the following steps:
The following steps are adopted at the time n:
e(n)＝d(n)-y(n)；
y(n)＝WT(n)X(n)；
Where e (n) is the error signal, d (n) is the desired signal, and y (n) is the desired output value; μ is a step size factor; w (n) is the filter coefficient vector estimation at time n; w (n+1) is an updated filter coefficient vector estimation value P (n) =x T (n) X (n), which is a power estimation value of the input signal; x (N) = [ X (N), X (N-1), X (N-n+1) ] is an input acceleration signal at time N; alpha is a positive constant.
Specifically, the algorithm comprises the following steps: firstly initializing P (0) and W (0), then reading X (n) and d (n), and inputting a reference signal to obtain y (n) through filtering, wherein y (n) =W T (n) X (n); re-calculating an error e (n), wherein e (n) =d (n) -y (n); recalculating P (n), where P (n) =x T (n) X (n), after which the matrix is updated to obtainThen continue reading X (n) and d (n) at the next instant.
Optionally, the gas circuit module 12 includes: a linear bleed valve; the linear air release valve is controlled by adjusting the duty ratio of the square wave, and a code is set in an interrupt function of the timer_B to control the closing and opening of the air valve. For example, the code is:
LINEARVA _s; closure of the linear valve
For (j=t; j > 0;j- -)// adjusting the size of j to adjust the deflation rate, the greater j deflates the slower
{
_delay_cycles(80)；
}
LINEARVA _o; linear opening
Taking 80 moments as a period, considering the difference of the deflation speed during use, in order to ensure the linear constant deflation speed, the size of the T value is regulated through pressure feedback acquired in real time, so that the aim of regulating the deflation speed is fulfilled. When the deflation speed is too fast, the value of T is increased, the deflation speed is reduced, and vice versa.
The following detailed description of embodiments of the present application is provided with reference to fig. 2 so that those skilled in the art to which the present application pertains can easily implement the present application. This application may be embodied in many different forms and is not limited to the embodiments described herein.
Fig. 2 is a schematic diagram of a blood pressure measurement system 20 according to the present application. Wherein the set 21 may implement the functionality of the set 11 in the embodiment of fig. 1, the air path module 22 may implement the air path module 12 in the embodiment of fig. 1, the pressure acquisition module 23 may implement the functionality of the pressure acquisition module 13 in the embodiment of fig. 1, the acceleration acquisition module 24 may implement the functionality of the acceleration acquisition module 14 in the embodiment of fig. 1, and the processing module 25 may implement the functionality of the processing module 15 in the embodiment of fig. 1.
The blood pressure measurement system 20 further includes: the safety module 26 is coupled to the air path module 22 and to the pressure signal acquisition module 23, and is configured to, when the pressure signal is detected to be too high by the pressure signal acquisition module 23, cause the air path module 22 to perform forced air release, so as to ensure safety of a user when the pressure is too high.
Optionally, the blood pressure measurement system further includes: a communication module 26, coupled to the processing module 25, for transmitting the blood pressure value to an external system. The external system may be an external system network communication such as an external terminal and a workstation, and specifically, receives the blood pressure value from the processing module 25 and communicates with external systems such as various cloud databases, service platforms, external terminals and monitoring systems, for example, with external terminals such as a desktop computer, a mobile phone, a notebook computer, a tablet computer, etc.
Similar to the principles of the above embodiments, the present application provides a blood pressure measurement method applied to an adaptive filtering blood pressure measurement system, the system comprising: the kit is provided with an air bag and is used for being fixed at a part to be measured; the gas circuit module is connected with the sleeve; for inflating and deflating the balloon; the pressure signal acquisition module is connected with the sleeve and is used for acquiring pressure signals in the sleeve; the acceleration acquisition module is used for acquiring acceleration data of the movement of the part to be detected in real time and outputting corresponding acceleration digital signals; the method comprises the following steps:
Filtering the pressure signal by using the acceleration digital signal as an adaptive filtering reference signal through an adaptive filtering method to obtain a filtering processing pressure signal;
Dividing the peak value sequence into two parts according to the maximum peak value reached by the detected peak value sequence of the filtering processing pressure signal, respectively obtaining a first envelope curve for judging the systolic pressure and a second envelope curve for judging the diastolic pressure through Gaussian fitting, further obtaining a corrected peak value sequence, and obtaining the systolic pressure and the diastolic pressure according to the corrected peak value sequence.
Specific embodiments are provided below with reference to the accompanying drawings:
fig. 3 is a schematic flow chart of a blood pressure measurement method according to an embodiment of the application.
The method comprises the following steps:
step S301: and filtering the pressure signal by using the acceleration digital signal as an adaptive filtering reference signal through an adaptive filtering method to obtain a filtering processing pressure signal.
Optionally, the collected pressure signal is received, wherein the pressure signal comprises a motion interference signal, and the pressure signal is filtered according to an adaptive filtering method by receiving the acceleration digital signal as an adaptive filtering reference signal, so as to obtain a filtered pressure signal.
Step S302: dividing the peak value sequence into two parts according to the maximum peak value reached by the detected peak value sequence of the filtering processing pressure signal, respectively obtaining a first envelope curve for judging the systolic pressure and a second envelope curve for judging the diastolic pressure through Gaussian fitting, further obtaining a corrected peak value sequence, and obtaining the systolic pressure and the diastolic pressure according to the corrected peak value sequence.
Optionally, according to the peak sequence of the wave detected by the obtained filtering signal, dividing the peak sequence into two parts by taking the maximum peak point of the peak sequence as a demarcation point, performing gaussian fitting on one part to obtain a first envelope, determining the systolic pressure according to the first envelope, performing gaussian fitting on the other part to obtain a second envelope, and determining the diastolic pressure according to the second envelope; wherein, in a cardiac cycle, ventricular systole causes the main arterial pressure to rise sharply and reach a maximum in the middle of the systole, the arterial pressure value at which is called systolic pressure; and ventricular diastole causes the aortic blood pressure to drop and reach a minimum at end diastole, where the arterial blood pressure value is the diastolic pressure. The mean arterial pressure is then the mean value of the arterial pressure during one cardiac cycle. The corresponding searching range of the characteristic points is determined according to the average pressure, namely, the fitting curve is brought into the previously stored time to obtain a new peak sequence, namely, a corrected peak sequence, and then a significant increase position and a significant decrease position are provided according to the pulse wave amplitude, and the systolic pressure and the diastolic pressure are respectively calculated corresponding to the points of the systolic pressure and the diastolic pressure corresponding to the sudden change of the pulse wave amplitude, so that the blood pressure value after interference filtering is obtained. The method not only solves the problem of poor individual adaptability, but also overcomes the influence of interference signals in the process of searching the characteristic points of the waveform characteristic method by using curve fitting, and improves the accuracy of searching the characteristic points, thereby improving the accuracy of blood pressure measurement.
Optionally, the adaptive filtering method utilizes an NLMS adaptive filtering algorithm for filtering; specifically, the collected pressure signal is received, wherein the pressure signal comprises a motion interference signal, and the pressure signal is filtered according to an NLMS adaptive filtering algorithm by receiving an acceleration digital signal as an adaptive filtering reference signal, so as to obtain a filtering processing pressure signal. The NLMS adaptive filtering algorithm is implemented by an adaptive filter.
In order to achieve the target filtering effect, the adaptive filter is designed according to the currently common adaptive filtering algorithm, such as the least Squares error algorithm (LEAST MEAN square, LMS), the normalized mean square error algorithm, the recursive least Squares algorithm (Recursive Least Squares, RLS), and the adaptive filtering of the frequency domain, and is typically the LMS and RLS algorithms. However, in most cases where adaptive filter processing is required, we cannot know the characteristics of the input signal, and the input signal changes over time, and it is impossible to directly measure the target filtering.
For this purpose, an improved algorithm NLMS (Normalized LMS, NLMS) algorithm is adopted, the core idea of which is to adjust the compensation factor μ according to the input n moment of the adaptive filter, n being proportional to the steady state error, μ being inversely proportional to the steady state error, and to reduce the steady state error by adjusting μ as the input n increases continuously.
Alternatively, we use an adaptive filter to filter using NLMS adaptive filtering algorithms. The NLMS adaptive filtering algorithm comprises the following steps:
The following steps are adopted at the time n:
e(n)＝d(n)-y(n)；
y(n)＝WT(n)X(n)；
Where e (n) is the error signal, d (n) is the desired signal, and y (n) is the desired output value; μ is a step size factor; w (n) is the filter coefficient vector estimation at time n; w (n+1) is an updated filter coefficient vector estimation value P (n) =x T (n) X (n), which is a power estimation value of the input signal; x (N) = [ X (N), X (N-1), X (N-n+1) ] is an input acceleration signal at time N; alpha is a positive constant.
Specifically, the algorithm comprises the following steps: firstly initializing P (0) and W (0), then reading X (n) and d (n), and inputting a reference signal to obtain y (n) through filtering, wherein y (n) =W T (n) X (n); re-calculating an error e (n), wherein e (n) =d (n) -y (n); recalculating P (n), where P (n) =x T (n) X (n), after which the matrix is updated to obtainThen continue reading X (n) and d (n) at the next instant.
As shown in fig. 4, a schematic structural diagram of a computer device 40 according to an embodiment of the present application is shown.
The computer device 40 includes: a memory 41 and a processor 42; the memory 41 is for storing a computer program; the processor 42 runs a computer program to implement the blood pressure measurement method as described in fig. 3.
Alternatively, the number of the memories 41 may be one or more, and the number of the processors 41 may be one or more, and one is taken as an example in fig. 4.
Optionally, the processor 42 in the electronic device 40 loads one or more instructions corresponding to the process of the application program into the memory 41 according to the steps as described in fig. 3, and the processor 42 executes the application program stored in the memory 41, so as to implement various functions in the blood pressure measurement method as described in fig. 3.
Optionally, the memory 41 may include, but is not limited to, high speed random access memory, nonvolatile memory. Such as one or more disk storage devices, flash memory devices, or other non-volatile solid-state storage devices; the processor 42 may include, but is not limited to, a central processing unit (Central Processing Unit, CPU), a network processor (Network Processor, NP), etc.; but may also be a digital signal processor (DIGITAL SIGNAL Processing, DSP), application Specific Integrated Circuit (ASIC), field-Programmable gate array (FPGA) or other Programmable logic device, discrete gate or transistor logic device, discrete hardware components.
Alternatively, the processor 42 may be a general-purpose processor, including a central processing unit (Central Processing Unit, abbreviated as CPU), a network processor (Network Processor, abbreviated as NP), and the like; but may also be a digital signal processor (DIGITAL SIGNAL Processing, DSP), application Specific Integrated Circuit (ASIC), field-Programmable gate array (FPGA) or other Programmable logic device, discrete gate or transistor logic device, discrete hardware components.
The present application also provides a computer readable storage medium storing a computer program which when run implements a blood pressure measurement method as shown in fig. 3. The computer-readable storage medium may include, but is not limited to, floppy diskettes, optical disks, CD-ROMs (compact disk-read only memories), magneto-optical disks, ROMs (read-only memories), RAMs (random access memories), EPROMs (erasable programmable read only memories), EEPROMs (electrically erasable programmable read only memories), magnetic or optical cards, flash memory, or other type of media/machine-readable medium suitable for storing machine-executable instructions. The computer readable storage medium may be an article of manufacture that is not accessed by a computer device or may be a component used by an accessed computer device.
In summary, the blood pressure measurement system, the blood pressure measurement method, the computer device and the storage medium of the present invention include: the kit is provided with an air bag and is used for being fixed at a part to be measured; the gas circuit module is connected with the sleeve; for inflating and deflating the balloon; the pressure signal acquisition module is connected with the sleeve and is used for acquiring pressure signals in the sleeve; the acceleration acquisition module is used for acquiring acceleration data of the movement of the part to be detected in real time and outputting corresponding acceleration digital signals; the processing module is in communication connection with the pressure signal acquisition module, the gas circuit module and the acceleration acquisition module, and is used for filtering the pressure signal by using the acceleration digital signal as an adaptive filtering reference signal through an adaptive filtering method to obtain a filtering processing pressure signal, dividing the peak sequence into two parts according to the maximum peak value reached by the peak sequence of the detected filtering processing pressure signal, respectively obtaining a first envelope curve for judging the systolic pressure and a second envelope curve for judging the diastolic pressure through Gaussian fitting, further obtaining a corrected peak value sequence, and obtaining the systolic pressure and the diastolic pressure according to the corrected peak value sequence. Therefore, the invention effectively overcomes various defects in the prior art and has high industrial utilization value.
The above embodiments are merely illustrative of the principles of the present invention and its effectiveness, and are not intended to limit the invention. Modifications and variations may be made to the above-described embodiments by those skilled in the art without departing from the spirit and scope of the invention. Accordingly, it is intended that all equivalent modifications and variations of the invention be covered by the claims, which are within the ordinary skill of the art, be within the spirit and scope of the present disclosure.
Claims (7)
1. A blood pressure measurement system, comprising:
The kit is provided with an air bag and is used for being fixed at a part to be measured;
the gas circuit module is connected with the sleeve; for inflating and deflating the balloon;
the pressure signal acquisition module is connected with the sleeve and is used for acquiring pressure signals in the sleeve;
the acceleration acquisition module is used for acquiring acceleration data of the movement of the part to be detected in real time and outputting corresponding acceleration digital signals;
The processing module is in communication connection with the pressure signal acquisition module, the gas circuit module and the acceleration acquisition module, and is used for filtering the pressure signal by using the acceleration digital signal as an adaptive filtering reference signal through an adaptive filtering method to obtain a filtering processing pressure signal; detecting pulse waves according to the obtained filtering processing pressure signals to obtain an original pulse wave crest sequence; determining a start point and an end point of the pulse wave according to the detected steep rising edge of the pulse wave, and obtaining the maximum value between the start point and the end point to determine the peak of the pulse wave; comparing the amplitude of the pulse wave with the interval between adjacent pulse waves, and removing singular pulse waves to obtain a modified pulse wave crest sequence; dividing the modified pulse wave crest sequence into two parts by taking the maximum peak point as a boundary, wherein the front part is singly subjected to Gaussian fitting to obtain a first envelope line for obtaining the systolic pressure, and the rear part is singly subjected to Gaussian fitting to obtain a second envelope line for obtaining the diastolic pressure; further obtaining a blood pressure measurement result;
Wherein, acceleration acquisition module includes: a sensing element, a conversion element, an amplifying circuit, and a component of one or more functions of the digital conversion element; when the sensing element is deformed due to the movement of the part to be detected, the conversion element measures the deformation of the sensing element to obtain acceleration data, then the acceleration data are converted into measurable acceleration electric signals, the acceleration electric signals are amplified by the amplifying circuit, the signal to noise ratio is improved, and finally the acceleration electric signals are digitally converted into acceleration digital signals to be output;
the way to remove the singular pulse wave includes:
Traversing the obtained original pulse wave crest sequence to obtain the intervals between all adjacent pulse waves, wherein the intervals are concentrated and gathered around a certain point, and the point far away from the certain point is regarded as an interference point; if the current pulse wave is closer to the previous pulse wave and the current pulse wave is closer to the next pulse wave, the point is regarded as an interference point; removing interference points;
If the current pulse wave amplitude is less than 80% or more than 120% of the average value of the front and rear pulse wave amplitudes, the average value is used to replace the current pulse wave amplitude.
2. The blood pressure measurement system of claim 1, wherein the adaptive filtering method utilizes an NLMS adaptive filtering algorithm for filtering.
3. The blood pressure measurement system of claim 2, wherein the NLMS adaptive filtering algorithm comprises:
The following steps are adopted at the time n:
e(n)＝d(n)-y(n)；
y(n)＝WT(n)X(n)；
Where e (n) is the error signal, d (n) is the desired signal, and y (n) is the desired output value; μ is a step size factor; w (n) is the filter coefficient vector estimation at time n; w (n+1) is an updated filter coefficient vector estimation value P (n) =x T (n) X (n), which is a power estimation value of the input signal; x (N) = [ X (N), X (N-1), X (N-n+1) ] is an input acceleration signal at time N; alpha is a positive constant.
4. The blood pressure measurement system of claim 1, wherein the air circuit module comprises: a linear bleed valve.
5. The blood pressure measurement system of claim 1, further comprising:
The safety module is coupled with the gas circuit module and the pressure signal acquisition module and is used for forcedly deflating when the pressure signal is detected to be too high;
or a communication module coupled to the processing module for transmitting the blood pressure measurement to an external system.
6. A computer apparatus, comprising:
One or more memories for storing computer programs;
One or more processors configured to implement the blood pressure measurement system functions of any one of claims 1 to 5.
7. A computer storage medium, characterized in that a computer program is stored, which computer program, when run, realizes the blood pressure measurement system function of any one of claims 1 to 5.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910386120.2A CN111904403B (en) | 2019-05-09 | 2019-05-09 | Blood pressure measurement system, blood pressure measurement method, computer device, and storage medium |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910386120.2A CN111904403B (en) | 2019-05-09 | 2019-05-09 | Blood pressure measurement system, blood pressure measurement method, computer device, and storage medium |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN111904403A CN111904403A (en) | 2020-11-10 |
| CN111904403B true CN111904403B (en) | 2024-08-06 |
Family
ID=73241855
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201910386120.2A Active CN111904403B (en) | 2019-05-09 | 2019-05-09 | Blood pressure measurement system, blood pressure measurement method, computer device, and storage medium |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN111904403B (en) |
Families Citing this family (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117643460B (en) * | 2024-01-29 | 2024-07-09 | 未来穿戴健康科技股份有限公司 | Blood pressure measuring device, blood pressure measuring apparatus, electronic device, and storage medium |
Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107850460A (en) * | 2015-03-13 | 2018-03-27 | 李新德 | The adaptive approach and system of detection signal from the data of disturbed pollution |
Family Cites Families (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101810475B (en) * | 2010-04-27 | 2012-02-15 | 哈尔滨工业大学 | Electronic auscultation sphygmomanometer based on combination of Korotkoff sound method and oscillometric method |
| JP6149548B2 (en) * | 2013-07-01 | 2017-06-21 | オムロンヘルスケア株式会社 | Electronic blood pressure monitor |
| CN103381092B (en) * | 2013-07-09 | 2015-07-22 | 深圳市理邦精密仪器股份有限公司 | Method and device for acquiring interference signals of non-invasive blood pressure measurement |
| CN103750832A (en) * | 2014-01-14 | 2014-04-30 | 上海交通大学 | Real-time wireless blood pressure monitoring system, blood pressure measuring device and blood pressure analysis method |
| CN104173036A (en) * | 2014-09-11 | 2014-12-03 | 重庆大学 | Pulse wave acquisition device, and non-invasive blood pressure continuous beat-to-beat measuring system and method |
| CN104382571B (en) * | 2014-10-28 | 2017-06-16 | 深圳市维亿魄科技有限公司 | A kind of measurement blood pressure method and device based on radial artery pulse wave conduction time |
| CN105852826B (en) * | 2016-03-22 | 2018-10-09 | 北京奇虎科技有限公司 | The method that terminal and terminal determine physiologic information |
| CN108209896A (en) * | 2016-12-22 | 2018-06-29 | 中国科学院沈阳自动化研究所 | A kind of Wrist blood pressure meter and its measuring method |
| EP3403572A1 (en) * | 2017-05-17 | 2018-11-21 | My-Vitality SàRL | Pulse wave diagnostic device and method of calculating and determining fatigue |
-
2019
- 2019-05-09 CN CN201910386120.2A patent/CN111904403B/en active Active
Patent Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107850460A (en) * | 2015-03-13 | 2018-03-27 | 李新德 | The adaptive approach and system of detection signal from the data of disturbed pollution |
Non-Patent Citations (1)
| Title |
|---|
| "NLMS 算法在有源降噪系统中的应用";刘姜涛，徐辉;《湖北第二师范学院学报》;第31卷(第2期);第1-2页 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN111904403A (en) | 2020-11-10 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| KR102007073B1 (en) | Continuous calibration of a blood pressure measurement device | |
| CN104116503B (en) | A kind of measurement apparatus of noinvasive continuous blood pressure | |
| US10092268B2 (en) | Method and apparatus to monitor physiologic and biometric parameters using a non-invasive set of transducers | |
| US20190104953A1 (en) | Blood pressure estimation using finger-wearable sensor array | |
| US5582179A (en) | Device to measure vascular function | |
| CN110301906A (en) | Device for non-invasively measuring blood pressure | |
| WO2017142668A1 (en) | Blood pressure estimation based on pulse wave velocity | |
| CN201157353Y (en) | Detection apparatus for blood pressure and bloodstream parameter | |
| CN107669256A (en) | Measuring method, the device and system of continuous blood pressure | |
| CN104042200B (en) | A kind of non-invasive monitoring devices and methods therefor of arteriotony by shooting | |
| CN114431840A (en) | Pulse acquisition device, pulse acquisition method and system | |
| CN105748056B (en) | blood pressure detection system | |
| Guo et al. | Assessment of a calibration-free method of cuffless blood pressure measurement: a pilot study | |
| CN110731783B (en) | A peak extraction method for heart rate estimation | |
| CN111904403B (en) | Blood pressure measurement system, blood pressure measurement method, computer device, and storage medium | |
| CN109497981A (en) | A Korotkoff sound blood pressure detection device with pulse wave detection and detection method thereof | |
| CN1985750A (en) | Pulse wave detecting method and device by means of cardiac symbol signal | |
| Ciaccio et al. | Tonometric arterial pulse sensor with noise cancellation | |
| CN113854988A (en) | Cardiovascular function detection method and system based on pulse waves | |
| CN110680298A (en) | Korotkoff sound electronic blood pressure measuring instrument and active noise reduction and pickup device, system and method thereof | |
| CN212261359U (en) | Ultrasonic wave double entry sphygmomanometer | |
| Jain et al. | Seismocardiography: An alternate method to estimate electro-mechanical window | |
| CN102415881A (en) | Blood pressure measuring method with pulse strength self-adaptive control | |
| US20220183573A1 (en) | Non-invasive method and system for measuring motion characteristics of myocardial tissue | |
| US20240074676A1 (en) | Wearable and portable system and method for measuring cardiac parameters for detecting cardiopathies |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |