CN108523867B - Self-calibration PPG non-invasive blood pressure measurement method and system - Google Patents
Self-calibration PPG non-invasive blood pressure measurement method and system Download PDFInfo
- Publication number
- CN108523867B CN108523867B CN201810262675.1A CN201810262675A CN108523867B CN 108523867 B CN108523867 B CN 108523867B CN 201810262675 A CN201810262675 A CN 201810262675A CN 108523867 B CN108523867 B CN 108523867B
- Authority
- CN
- China
- Prior art keywords
- blood pressure
- ppg
- measurement
- age
- calibration
- 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
Images
Classifications
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/02—Detecting, measuring or recording pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography or electroauscultation; Heart catheters for measuring blood pressure
- A61B5/021—Measuring pressure in heart or blood vessels
- A61B5/02108—Measuring pressure in heart or blood vessels from analysis of pulse wave characteristics
- A61B5/02125—Measuring pressure in heart or blood vessels from analysis of pulse wave characteristics of pulse wave propagation time
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/0002—Remote monitoring of patients using telemetry, e.g. transmission of vital signals via a communication network
- A61B5/0004—Remote monitoring of patients using telemetry, e.g. transmission of vital signals via a communication network characterised by the type of physiological signal transmitted
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/68—Arrangements of detecting, measuring or recording means, e.g. sensors, in relation to patient
- A61B5/6801—Arrangements of detecting, measuring or recording means, e.g. sensors, in relation to patient specially adapted to be attached to or worn on the body surface
- A61B5/6802—Sensor mounted on worn items
- A61B5/681—Wristwatch-type devices
-
- 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
- A61B5/7246—Details of waveform analysis using correlation, e.g. template matching or determination of similarity
Landscapes
- Health & Medical Sciences (AREA)
- Life Sciences & Earth Sciences (AREA)
- Engineering & Computer Science (AREA)
- General Health & Medical Sciences (AREA)
- Veterinary Medicine (AREA)
- Biophysics (AREA)
- Biomedical Technology (AREA)
- Heart & Thoracic Surgery (AREA)
- Medical Informatics (AREA)
- Molecular Biology (AREA)
- Surgery (AREA)
- Animal Behavior & Ethology (AREA)
- Physics & Mathematics (AREA)
- Public Health (AREA)
- Pathology (AREA)
- Physiology (AREA)
- Cardiology (AREA)
- Computer Networks & Wireless Communication (AREA)
- Vascular Medicine (AREA)
- Artificial Intelligence (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Psychiatry (AREA)
- Signal Processing (AREA)
- Measuring Pulse, Heart Rate, Blood Pressure Or Blood Flow (AREA)
Abstract
The invention relates to a self-calibration PPG non-invasive blood pressure measurement method and a system, wherein the method comprises the following steps of S1, measuring according to the linear relation between pulse wave conduction time and blood pressure to obtain a PPG blood pressure measurement value; and S2, calibrating the PPG blood pressure measurement value according to the blood pressure calibration model and the personal sign information, and calculating to obtain a blood pressure calibration value. According to the self-calibration PPG non-invasive blood pressure measurement method, the PPG blood pressure measurement value is obtained through the pulse wave and the electrocardiosignal measurement reflected by the PPG, and then the measurement efficiency and the measurement result are improved by calibrating the PPG blood pressure measurement value according to the blood pressure calibration model and the personal sign information, so that the blood pressure measurement result is less interfered, more accurate and has higher reference value.
Description
Technical Field
The invention relates to the field of blood pressure measurement, in particular to a self-calibration PPG non-invasive blood pressure measurement method and system.
Background
Nowadays, hypertension has become the most common chronic disease of the cardiovascular system, and is one of the global public problems. Blood pressure measuring devices used in hospitals and families are mainly based on a korotkoff sound method or an oscillometric method, although blood pressure values can be measured accurately, cuff inflation and deflation are needed, only blood pressure values at a certain moment can be measured, and continuous monitoring of blood pressure cannot be carried out. The principle of the current PPG technique is that the LED emits light to the skin, the light reflected back through the skin tissue is received by the photosensor and converted into an electrical signal, which is then converted into a digital signal by AD, and the absorption of light naturally changes due to the flow of blood in the artery. When we convert light into an electrical signal, it is because the absorption of light by arteries changes and the absorption of light by other tissues is basically unchanged, and the resulting signal can be divided into a Direct Current (DC) signal and an Alternating Current (AC) signal. The AC signal is extracted to reflect the characteristics of blood flow.
In the process of pulse signal measurement, due to the influence of various complex factors (for example, movement of a measurement part, natural light, fluorescent light and other interference, the measured signal is often interfered to affect the measurement accuracy), the detected signal generally contains a large amount of noise. Therefore, noise processing of the signal is required. The noise reduction method mainly comprises a hardware filtering method and a software filtering method. The hardware filtering is mainly implemented by using a filtering circuit to filter the noise frequency part in the signal, and the software filtering is usually based on some methods of Fourier transform principle, such as FFT analysis, cepstrum analysis, short-time Fourier analysis, Wigner analysis, and the like. However, most of the noise of the pulse signal is unstable or abrupt weak signal, and the waveform is widened by hardware filtering and Fourier transform software filtering while the noise is reduced, so that the weak abrupt change information of the pulse signal characteristics contained in the signal is smoothed and even erased, and the measurement accuracy is influenced.
Disclosure of Invention
The invention aims to solve the technical problem of providing a self-calibration PPG non-invasive blood pressure measurement method and system, which can obtain a more accurate blood pressure value.
The technical scheme for solving the technical problems is as follows: a self-calibration PPG non-invasive blood pressure measurement method comprises the following steps,
s1, obtaining a PPG blood pressure measurement value according to the linear relation measurement between the pulse wave conduction time and the blood pressure;
and S2, calibrating the PPG blood pressure measurement value according to the blood pressure calibration model and the personal sign information, and calculating to obtain a blood pressure calibration value.
The invention has the beneficial effects that: according to the self-calibration PPG non-invasive blood pressure measurement method, the PPG blood pressure measurement value is obtained through the pulse wave and the electrocardiosignal measurement reflected by the PPG, and then the measurement efficiency and the measurement result are improved by calibrating the PPG blood pressure measurement value according to the blood pressure calibration model and the personal sign information, so that the blood pressure measurement result is less interfered, more accurate and has higher reference value.
On the basis of the technical scheme, the invention can be further improved as follows.
Further, before the step S2, the method further comprises
Collecting blood pressure measurement data of a plurality of users, and extracting a plurality of personal sign information of each user;
respectively taking the multiple items of personal sign information of each user as characteristic parameters, and statistically analyzing the correlation between the multiple items of personal sign information of each user and the blood pressure measurement data of the corresponding user by using the SPSS to obtain one characteristic parameter with the best correlation with the blood pressure;
and performing regression analysis by taking the characteristic parameter with the best correlation with the blood pressure as a variable to obtain a blood pressure calibration model.
Further, the personal sign information comprises age, gender and BMI, and the characteristic parameters based on the age are best related to the blood pressure.
The beneficial effect of adopting the further scheme is that: the statistical analysis is carried out on the blood pressure data collected clinically to obtain that the age of an individual is greatly correlated with the blood pressure, and then the individual age is combined to calibrate the PPG blood pressure measurement value to improve the measurement efficiency and result, so that the interference on the blood pressure measurement result is smaller, the accuracy is higher, and the reference value is higher.
Further, the blood pressure calibration model is that,
SBP＝sbp±0.33*age
DBP＝dbp±0.14*age
wherein SBP and DBP are measured values of high and low PPG blood pressure obtained by the current measurement, age is age, and SBP and DBP are calibrated values of high and low blood pressure obtained by the current calculation.
Further, the personal sign information also comprises a systolic pressure and a diastolic pressure obtained by clinical measurement, and the systolic pressure and the diastolic pressure obtained by clinical measurement are used as an initial PPG blood pressure measurement value.
Based on the self-calibration PPG non-invasive blood pressure measurement method, the invention also provides a self-calibration PPG non-invasive blood pressure measurement system.
A self-calibration PPG non-invasive blood pressure measurement system comprises a PPG blood pressure measurement module and a PPG blood pressure calibration module,
the PPG blood pressure measurement module is used for measuring and obtaining a PPG blood pressure measurement value according to the linear relation between the pulse wave conduction time and the blood pressure;
and the PPG blood pressure calibration module is used for calibrating the PPG blood pressure measurement value according to a blood pressure calibration model and personal sign information, and calculating to obtain a blood pressure calibration value.
The invention has the beneficial effects that: the self-calibration PPG non-invasive blood pressure measurement system firstly obtains a PPG blood pressure measurement value through the pulse wave and electrocardiosignal measurement reflected by the PPG, and then calibrates the PPG blood pressure measurement value according to the blood pressure calibration model and the personal sign information to improve the measurement efficiency and result, so that the blood pressure measurement result is less interfered, more accurate and has higher reference value.
On the basis of the technical scheme, the invention can be further improved as follows.
Further, the blood pressure calibration model generation module is also included and is used for generating the blood pressure calibration model
Collecting blood pressure measurement data of a plurality of users, and extracting a plurality of personal sign information of each user;
respectively taking the multiple items of personal sign information of each user as characteristic parameters, and statistically analyzing the correlation between the multiple items of personal sign information of each user and the blood pressure measurement data of the corresponding user by using the SPSS to obtain one characteristic parameter with the best correlation with the blood pressure;
and performing regression analysis by taking the characteristic parameter with the best correlation with the blood pressure as a variable to obtain a blood pressure calibration model.
Further, the personal sign information comprises age, gender and BM I, and the characteristic parameter based on the age is best related to the blood pressure.
The beneficial effect of adopting the further scheme is that: the statistical analysis is carried out on the blood pressure data collected clinically to obtain that the age of an individual is greatly correlated with the blood pressure, and then the individual age is combined to calibrate the PPG blood pressure measurement value to improve the measurement efficiency and result, so that the interference on the blood pressure measurement result is smaller, the accuracy is higher, and the reference value is higher.
Further, the blood pressure calibration model specifically comprises:
SBP＝sbp±0.33*age
DBP＝dbp±0.14*age
wherein SBP and DBP are measured values of high and low PPG blood pressure obtained by the current measurement, age is age, and SBP and DBP are calibrated values of high and low blood pressure obtained by the current calculation.
Further, the personal sign information also comprises a systolic pressure and a diastolic pressure obtained by clinical measurement, and the systolic pressure and the diastolic pressure obtained by clinical measurement are used as an initial PPG blood pressure measurement value.
Drawings
FIG. 1 is a flow chart of a self-calibrating PPG non-invasive blood pressure measurement method of the present invention;
FIG. 2 is a flow chart of an embodiment of a self-calibrating PPG non-invasive blood pressure measurement method of the present invention;
FIG. 3 is a block diagram of a self-calibrating PPG non-invasive blood pressure measurement system of the present invention;
Detailed Description
The principles and features of this invention are described below in conjunction with the following drawings, which are set forth by way of illustration only and are not intended to limit the scope of the invention.
As shown in fig. 1, a self-calibration PPG non-invasive blood pressure measurement method, comprises the following steps,
s1, obtaining a PPG blood pressure measurement value according to the linear relation measurement between the pulse wave conduction time and the blood pressure;
and S2, calibrating the PPG blood pressure measurement value according to the blood pressure calibration model and the personal sign information, and calculating to obtain a blood pressure calibration value.
In S1, the linear relationship between Pulse Transit Time (PTT) and blood pressure is derived as follows:
tomas Yang, 1808, proposed the formula for the propagation velocity of blood in the elastic lumen of blood vessels:
h is the thickness of the vessel wall; d is the inner diameter of the blood vessel; e is the Young's modulus of elasticity of the blood vessel; ρ is the blood density. In 1878, Moens and Korteweg performed experiments on the pulse wave propagation velocity, and the pulse wave propagation velocity calculation formula was proposed as follows:
according to the experimental results, the moens constant K is proposed as a dimensionless empirical value, which is 0.8 for the human aorta. In 1957, Lansdown proposed that the pulse wave transit time of the same individual is linearly related to the blood pressure within a certain time and range, and is relatively stable. And because the relationship between the pulse wave propagation time and the pulse wave propagation velocity can be expressed by the following formula (3):
s is the pulse wave propagation distance, and T is the pulse wave propagation time.
Hughes et al derived the relationship between Young's modulus of elasticity and blood pressure of arterial vessel wall to obtain formula (4):
in the formula (4), E0Is the modulus of elasticity at pressure zero, P is the blood pressure value, γ is a quantity characterizing the blood vessel characteristics, and the value is in the range of 0.016-0.018 (mmHg-1). Combining the Moens-Korteweg pulse wave velocity equation and the equation derived from Hughes, one can obtain:
wherein a is the coefficient of the model, reflects different vascular states, and is determined by analyzing experimental measurement data, and T is the pulse wave conduction time.
Assuming that the wall of the artery vessel is an ideal elastic material, neglecting the influence of the variation of undetectable parameters such as blood viscosity, density and the like, a relation model of blood pressure and pulse wave conduction time can be obtained:
where Δ P is the amount of change in blood pressure, the above formula may be changed to formula (7):
BP＝BP0+b*(T-T0) (7)
the approximately linear relationship between the blood pressure and the pulse wave propagation time can be deduced:
BP＝a+b*T (8)
before S2, a step of calibrating a blood pressure model is further included, specifically as follows:
extracting age, sex, BMI (weight/height) of user2) And as characteristic parameters, carrying out SPSS statistical analysis on blood pressure measurement data of about 65000 users to analyze the correlation between the characteristic parameters and the blood pressure, finding out one characteristic parameter with the best correlation with the blood pressure, carrying out regression analysis by taking the one characteristic parameter with the best correlation with the blood pressure as a variable, and establishing a regression equation (namely a blood pressure calibration model) for calibrating the blood pressure.
After performing blood pressure correlation analysis experiments on age, gender and BMI, it is shown in table 1 that the correlation between age and SBP and DBP is the best, i.e., R is 0.45 and R is 0.35(R is the fitting radius); BM I exhibits a weak correlation with blood pressure; gender and blood pressure were not statistically significant.
TABLE 1 Person correlation between characteristic parameters and blood pressure
| SBP | DBP | |
| Sex | -0.02 | -0.018 |
| Age | 0.45 | 0.35 |
| BMI | 0.2 | 0.18 |
Using the characteristic parameters, a linear regression equation is established as a relation for blood pressure estimation, i.e.
SBP＝asbp*Age+bsbp
DBP＝adbp*Age+bdbp
a is a regression coefficient, bsbpAnd bdbpAge is Age, and SBP and DBP are high and low blood pressure calibration values obtained by calculation.
Regression analysis is carried out on Age, SBP and DBP respectively to obtain asbp＝±0.33，adbpR is 0.63 and 0.55, respectively, ± 0.14, i.e. more than half of the data can be fit, thus yielding a blood pressure calibration model:
SBP＝sbp±0.33*age
DBP＝dbp±0.14*age
wherein ± 0.33 × ge is a calibration parameter of the high voltage, and ± 0.14 × ge is a calibration parameter of the low voltage.
Specifically, if the measured value of the PPG blood pressure obtained by the current measurement is greater than the measured value of the PPG blood pressure obtained by the last measurement, the measurement is performed
SBP＝sbp+0.33*age (9)
DBP＝dbp+0.14*age (10)
If the PPG blood pressure measured value obtained by the measurement is smaller than the PPG blood pressure measured value obtained by the previous measurement, the measurement is carried out on the PPG blood pressure measured value
SBP＝sbp-0.33*age (11)
DBP＝dbp-0.14*age (12)
Wherein SBP and DBP are measured values of high and low PPG blood pressure obtained by the current measurement, age is the age of the individual, and SBP and DBP are calibrated values of high and low blood pressure obtained by the current calculation.
In addition, the personal sign information comprises a clinically measured systolic pressure and diastolic pressure, and the clinically measured systolic pressure and diastolic pressure are used as an initial PPG blood pressure measurement value. For example: when a group of PPG blood pressure measurement values are obtained according to the linear relation between the pulse wave conduction time and the blood pressure for the first time, the systolic pressure and the diastolic pressure obtained by clinical measurement are used as initial PPG blood pressure measurement values in the current time, the first PPG blood pressure measurement value is compared with the initial PPG blood pressure measurement value, and if the first PPG blood pressure measurement value is larger than the initial PPG blood pressure measurement value, the initial PPG blood pressure measurement value is obtained
SBP＝sbp+0.33*age
DBP＝dbp+0.14*age
If the PPG blood pressure measured value obtained by the first measurement is smaller than the initial PPG blood pressure measured value, the initial PPG blood pressure measured value is obtained
SBP＝sbp-0.33*age
DBP＝dbp-0.14*age
The method of the invention starts from the perspective of monitoring the individual blood pressure with more accurate trend, and considers that the single PPG technology can not reflect the individual blood pressure trend more accurately, thereby providing the secondary calibration and correction based on the individual characteristics of the individual.
The invention obtains the measured blood pressure value of the human body by calculating the transmission time of the pulse wave between two points based on the physiological mechanism of the blood pressure and the pulse wave, namely the linear relation between the blood pressure and the pulse wave transmission time (particularly the pulse wave transmission time between the arm and the wrist).
This specific embodiment can utilize PPG technique to measure the real-time blood pressure who obtains the individual in the bracelet, and the blood pressure that will measure through wireless bluetooth mode is transmitted user APP and is saved temporarily. After the APP obtains the measured blood pressure value, the measured blood pressure value is calibrated according to the formulas (9) - (12) by combining with the age of the user, and a more accurate real-time blood pressure value is obtained through calculation. Then, the obtained blood pressure value is fed back to wearable equipment through a wireless technology to be displayed, and meanwhile, the APP related interface displays a result and pushes a background to feed back suggestions and related protective measures.
Fig. 2 is a flowchart of an embodiment of a self-calibration PPG non-invasive blood pressure measurement method of the present invention.
Specifically, the self-calibration rectification can be realized by the following processes:
1. downloading a registration related APP (APP related to blood pressure measurement, such as a Maidong APP), and binding an intelligent blood pressure measurement bracelet (such as a Maidong intelligent bracelet);
2. wearing the bracelet on the 2 inch Neiguan acupoint on the transverse striation of the wrist;
3. after binding is successful, inputting age and high pressure and low pressure measured by other blood pressure equipment of the individual at that time, and writing the data into the bracelet through Bluetooth transmission;
4. starting a timer task in the bracelet, and automatically starting integral point measurement every time when an integral point is reached, such as 12 points and 13 points of Beijing time;
5. at the moment, the sensor is turned on by the bracelet, the green light on the back of the bracelet is turned on, and the measurement is started;
6. if the sensor chip returns to prompt that the measurement is successful within 1 minute, executing the step 7, otherwise, ending the measurement and closing the sensor;
7. the measurement is successful, the data (high voltage, low voltage, measurement time) is written into the hand ring ROM for storage, the data is compared with the last measurement data stored in the hand ring, and y is usedt_sbp、yt_dbpRespectively representing the high and low PPG blood pressure measured values obtained by the measurement, and using y(t-1)_sbp、y(t-1)_dbpAre respectively provided withRepresenting the high and low PPG blood pressure measurements from the last measurement. If yt_sbp>y(t-1)_sbpThat is, the measured value of the high PPG blood pressure is increased relative to the last time, the final corrected value y of the high blood pressure is obtainedsbp＝yt_sbp+ age 0.33; if yt_sbp<y(t-1)_sbpThat is, the measured value of the PPG blood pressure is decreased relative to the last time, the final corrected value y of the hypertension is obtainedsbp＝yt_sbp-age 0.33; if yt_dbp>y(t-1)_dbpI.e. the low PPG blood pressure measurement value is increased relative to the last time, the final low blood pressure calibration value ydbp＝yt_dbp+ age 0.14; if yt_dbp<y(t-1)_dbpI.e. the low PPG blood pressure measurement value is reduced relative to the last time, the final low blood pressure calibration value ydbp＝yt_dbp-age 0.14;
8. returning the final result value y by Bluetooth transmissionsbp、ydbpAnd measuring time;
9. and closing the sensor to finish the measurement.
According to the self-calibration PPG non-invasive blood pressure measurement method, firstly, a group of PPG blood pressure measurement values are obtained through pulse waves and electrocardiosignals reflected by PPG, then, statistical analysis is carried out on blood pressure data acquired clinically to obtain great correlation between the age of a person and blood pressure, and then the PPG blood pressure measurement values are calibrated in combination with the age of the person to improve the measurement efficiency and the measurement result, so that the interference on the blood pressure measurement result is smaller, the accuracy is higher, and the reference value is higher.
Based on the self-calibration PPG non-invasive blood pressure measurement method, the invention also provides a self-calibration PPG non-invasive blood pressure measurement system.
As shown in fig. 3, a self-calibration PPG non-invasive blood pressure measurement system comprises a PPG blood pressure measurement module and a PPG blood pressure calibration module,
the PPG blood pressure measurement module is used for measuring and obtaining a PPG blood pressure measurement value according to the linear relation between the pulse wave conduction time and the blood pressure;
and the PPG blood pressure calibration module is used for calibrating the PPG blood pressure measurement value according to a blood pressure calibration model and personal sign information, and calculating to obtain a blood pressure calibration value.
In this particular embodiment:
the invention also comprises a blood pressure calibration model generation module for generating a blood pressure calibration model
Collecting blood pressure measurement data of a plurality of users, and extracting a plurality of personal sign information of each user;
respectively taking the multiple items of personal sign information of each user as characteristic parameters, and statistically analyzing the correlation between the multiple items of personal sign information of each user and the blood pressure measurement data of the corresponding user by using the SPSS to obtain one characteristic parameter with the best correlation with the blood pressure;
and performing regression analysis by taking the characteristic parameter with the best correlation with the blood pressure as a variable to obtain a blood pressure calibration model.
The personal sign information comprises age, gender and BMI, and the characteristic parameters based on the age are best related to the blood pressure.
The blood pressure calibration model specifically comprises the following steps:
SBP＝sbp±0.33*age
DBP＝dbp±0.14*age
wherein SBP and DBP are measured values of high and low PPG blood pressure obtained by the current measurement, age is age, and SBP and DBP are calibrated values of high and low blood pressure obtained by the current calculation.
The personal sign information also comprises a systolic pressure and a diastolic pressure which are obtained by clinical measurement, and the systolic pressure and the diastolic pressure which are obtained by clinical measurement are used as an initial PPG blood pressure measurement value.
According to the self-calibration PPG non-invasive blood pressure measurement system, a group of PPG blood pressure measurement values are obtained through pulse waves and electrocardiosignals reflected by PPG, then the correlation between the age of a person and the blood pressure is obtained through statistical analysis of blood pressure data acquired clinically, and the measurement efficiency and the measurement result are improved by calibrating the PPG blood pressure measurement values according to the age of the person, so that the interference on the blood pressure measurement result is smaller, the accuracy is higher, and the reference value is higher.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents, improvements and the like that fall within the spirit and principle of the present invention are intended to be included therein.
Claims (2)
1. A self-calibration PPG non-invasive blood pressure measurement system is characterized in that: comprises a PPG blood pressure measuring module and a PPG blood pressure calibrating module,
the PPG blood pressure measurement module is used for measuring and obtaining a PPG blood pressure measurement value according to the linear relation between the pulse wave conduction time and the blood pressure;
the PPG blood pressure calibration module is used for calibrating the PPG blood pressure measurement value according to a blood pressure calibration model and personal sign information, and calculating to obtain a blood pressure calibration value;
the blood pressure calibration model generation module is used for acquiring blood pressure measurement data of a plurality of users and extracting a plurality of personal sign information of each user;
respectively taking the multiple items of personal sign information of each user as characteristic parameters, and statistically analyzing the correlation between the multiple items of personal sign information of each user and the blood pressure measurement data of the corresponding user by using the SPSS to obtain one characteristic parameter with the best correlation with the blood pressure;
taking a characteristic parameter with the best correlation with the blood pressure as a variable to carry out regression analysis to obtain a blood pressure calibration model; the personal sign information comprises age, gender and BMI, and the characteristic parameters based on the age are best correlated with the blood pressure;
the blood pressure calibration model specifically comprises the following steps:
SBP＝sbp±0.33*age
DBP＝dbp±0.14*age
wherein, ± 0.33 × age is calibration parameter of high pressure, ± 0.14 × age is calibration parameter of low pressure; in particular, the method comprises the following steps of,
if the PPG blood pressure measured value obtained by the measurement is larger than the PPG blood pressure measured value obtained by the measurement last time, the PPG blood pressure measured value is obtained
SBP＝sbp+0.33*age
DBP＝dbp+0.14*age
If the PPG blood pressure measured value obtained by the measurement is smaller than the PPG blood pressure measured value obtained by the previous measurement, the measurement is carried out on the PPG blood pressure measured value
SBP＝sbp-0.33*age
DBP-0.14 × age, wherein SBP is the measured value of high PPG blood pressure obtained by the current measurement, DBP is the measured value of low PPG blood pressure obtained by the current measurement, age is age, SBP is the calibrated value of high blood pressure obtained by the current calculation, and DBP is the calibrated value of low blood pressure obtained by the current calculation.
2. A self-calibrating PPG non-invasive blood pressure measurement system according to claim 1, wherein: the personal sign information also comprises systolic pressure and diastolic pressure obtained by clinical measurement, the systolic pressure obtained by clinical measurement is used as an initial high PPG blood pressure measurement value, and the diastolic pressure obtained by clinical measurement is used as an initial low PPG blood pressure measurement value.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810262675.1A CN108523867B (en) | 2018-03-28 | 2018-03-28 | Self-calibration PPG non-invasive blood pressure measurement method and system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810262675.1A CN108523867B (en) | 2018-03-28 | 2018-03-28 | Self-calibration PPG non-invasive blood pressure measurement method and system |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN108523867A CN108523867A (en) | 2018-09-14 |
| CN108523867B true CN108523867B (en) | 2020-12-29 |
Family
ID=63485342
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201810262675.1A Active CN108523867B (en) | 2018-03-28 | 2018-03-28 | Self-calibration PPG non-invasive blood pressure measurement method and system |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN108523867B (en) |
Families Citing this family (13)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109730663B (en) * | 2018-12-04 | 2022-07-12 | 上海大学 | Blood pressure evaluation method based on pulse wave conduction velocity nonlinear analysis |
| CN109872820B (en) * | 2019-03-29 | 2023-12-08 | 广州视源电子科技股份有限公司 | Method, device, equipment and storage medium for measuring blood pressure without cuff |
| CN110037673B (en) * | 2019-05-13 | 2020-12-01 | 深圳六合六医疗器械有限公司 | Statistical method and device for blood pressure personalized interval |
| CN110141201B (en) * | 2019-05-14 | 2020-07-24 | 中国科学院深圳先进技术研究院 | Blood pressure estimation method and device |
| CN110251105B (en) * | 2019-06-12 | 2022-06-21 | 广州视源电子科技股份有限公司 | Noninvasive blood pressure measuring method, device, equipment and system |
| CN110974199B (en) * | 2019-11-27 | 2022-07-08 | 英华达（上海）科技有限公司 | Calibration method, device and system for blood pressure measurement, electronic equipment and storage medium |
| CN111000537B (en) * | 2019-12-24 | 2022-05-27 | 中国人民解放军陆军军医大学第一附属医院 | Method for correcting influence of age, sex and blood pressure on pulse wave propagation speed |
| CN111986809A (en) * | 2020-08-10 | 2020-11-24 | 武汉麦咚健康科技有限公司 | Hypertension drug recommendation system and method for doctor-assisted judgment |
| CN112006669B (en) * | 2020-08-19 | 2021-06-04 | 北京雪扬科技有限公司 | Blood pressure meter based on double-channel calculation method of blood pressure measurement model |
| EP4039182B1 (en) * | 2020-12-09 | 2023-09-13 | Shenzhen Goodix Technology Co., Ltd. | Blood pressure measurement method and apparatus, and electronic device |
| CN113171071B (en) * | 2021-03-05 | 2022-02-15 | 上海立阖泰医疗科技有限公司 | Blood pressure measurement watch based on PWTT |
| CN113171068B (en) * | 2021-03-05 | 2022-02-18 | 上海立阖泰医疗科技有限公司 | Dynamic continuous blood pressure measurement watch based on blood pressure virtual calibration value |
| CN115336990B (en) * | 2022-08-09 | 2023-08-25 | 苏州国科医工科技发展(集团)有限公司 | Multi-point calibration-based sleeveless dynamic blood pressure measurement method |
Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102397064A (en) * | 2011-12-14 | 2012-04-04 | 中国航天员科研训练中心 | Continuous blood pressure measuring device |
| CN104116503A (en) * | 2014-07-16 | 2014-10-29 | 华中科技大学 | Noninvasive continuous blood pressure measuring method and device |
| CN104873186A (en) * | 2015-04-17 | 2015-09-02 | 中国科学院苏州生物医学工程技术研究所 | Wearable artery detection device and data processing method thereof |
| WO2016135202A1 (en) * | 2015-02-27 | 2016-09-01 | Preventicus Gmbh | Apparatus and method for determining blood pressure |
| CN106580303A (en) * | 2016-11-22 | 2017-04-26 | 浙江脉联医疗设备有限公司 | Method for correcting systolic pressure-related pulse wave propagation time |
| CN106618504A (en) * | 2017-01-19 | 2017-05-10 | 陈妍 | High-accuracy continuous non-invasive blood pressure measuring device with self-adaptation calibration function |
| WO2018025257A1 (en) * | 2016-08-02 | 2018-02-08 | ChroniSense Medical Ltd. | Blood pressure measurement using a wearable device |
Family Cites Families (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| NL1001309C2 (en) * | 1995-09-28 | 1997-04-03 | Tno | Method and device for the determination of brachial artery pressure wave on the basis of non-invasively measured finger blood pressure wave. |
| CN106793962A (en) * | 2014-09-05 | 2017-05-31 | 雷克兰德创投发展有限公司 | Method and apparatus for continuously estimating human blood-pressure using video image |
| CN204515353U (en) * | 2015-03-31 | 2015-07-29 | 深圳市长桑技术有限公司 | A kind of intelligent watch |
| CN104504297A (en) * | 2015-01-21 | 2015-04-08 | 甘肃百合物联科技信息有限公司 | Method for using neural network to forecast hypertension |
| CN106691406A (en) * | 2017-01-05 | 2017-05-24 | 大连理工大学 | Detection method of vascular elasticity and blood pressure based on single probe photoplethysmography pulse wave |
| CN107174225A (en) * | 2017-06-30 | 2017-09-19 | 哈尔滨工业大学深圳研究生院 | A kind of arm belt blood vessel physiologic parameter monitoring device |
-
2018
- 2018-03-28 CN CN201810262675.1A patent/CN108523867B/en active Active
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102397064A (en) * | 2011-12-14 | 2012-04-04 | 中国航天员科研训练中心 | Continuous blood pressure measuring device |
| CN104116503A (en) * | 2014-07-16 | 2014-10-29 | 华中科技大学 | Noninvasive continuous blood pressure measuring method and device |
| WO2016135202A1 (en) * | 2015-02-27 | 2016-09-01 | Preventicus Gmbh | Apparatus and method for determining blood pressure |
| CN104873186A (en) * | 2015-04-17 | 2015-09-02 | 中国科学院苏州生物医学工程技术研究所 | Wearable artery detection device and data processing method thereof |
| WO2018025257A1 (en) * | 2016-08-02 | 2018-02-08 | ChroniSense Medical Ltd. | Blood pressure measurement using a wearable device |
| CN106580303A (en) * | 2016-11-22 | 2017-04-26 | 浙江脉联医疗设备有限公司 | Method for correcting systolic pressure-related pulse wave propagation time |
| CN106618504A (en) * | 2017-01-19 | 2017-05-10 | 陈妍 | High-accuracy continuous non-invasive blood pressure measuring device with self-adaptation calibration function |
Non-Patent Citations (4)
| Title |
|---|
| Neuhauser HK ET AL.《Calibration of blood pressure data after replacement of the standard mercury sphygmomanometer by an oscillometric device and concurrent change of cuffs》.《Blood Press Monit》.2015, * |
| Youngzoon Yoon ET AL.《Non-constrained Blood Pressure Monitoring Using ECG and PPG for Personal Healthcare》.《Journal of Medical Systems》.2008, * |
| 高伟.《基于脉搏波的连续血压监测仪器的设计》.《中国优秀硕士学位论文全文数据库工程科技Ⅱ辑》.2017, * |
| 黄雯 等.《上海居民年龄与收缩压、舒张压、脉压的相关研究》.《上海护理》.2016,第16卷(第7期), * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN108523867A (en) | 2018-09-14 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN108523867B (en) | Self-calibration PPG non-invasive blood pressure measurement method and system | |
| US20220296176A1 (en) | Processing biological data | |
| Esmaili et al. | Nonlinear cuffless blood pressure estimation of healthy subjects using pulse transit time and arrival time | |
| CN112274126B (en) | Noninvasive continuous blood pressure detection method and device based on multiple pulse waves | |
| CN108185996B (en) | Arterial blood vessel age estimation model construction method and device | |
| CN109069031B (en) | Device and method for determining blood pressure of a subject | |
| Ye et al. | Estimation of systolic and diastolic pressure using the pulse transit time | |
| EP3061392B1 (en) | Blood pressure measurement | |
| US11006885B2 (en) | Apparatus for determining blood pressure | |
| US20170360313A1 (en) | Diastolic Blood Pressure Measurement Calibration | |
| WO2017016245A1 (en) | Blood pressure calculation method based on pulse reflected wave transit time, and blood pressure meter | |
| WO2017066149A1 (en) | Ambulatory blood pressure and vital sign monitoring apparatus, system and method | |
| WO2017092020A1 (en) | Blood pressure measurement method and apparatus | |
| CN1698536A (en) | Cuff-less type blood pressure continuous measuring method using automatic compensation | |
| US8414500B2 (en) | Arteriosclerosis diagnostic device | |
| US10470717B2 (en) | Pulse validation | |
| Shukla et al. | Noninvasive cuffless blood pressure measurement by vascular transit time | |
| CN112274120A (en) | Noninvasive arteriosclerosis detection method and device based on one-way pulse wave | |
| Song et al. | Estimation of blood pressure using photoplethysmography on the wrist | |
| CN210095711U (en) | Noninvasive continuous blood pressure measuring equipment | |
| Nagy et al. | Sensor fusion for the accurate non-invasive measurement of blood pressure | |
| Lui et al. | A novel calibration procedure of pulse transit time based blood pressure measurement with heart rate and respiratory rate | |
| Anchan | Estimating pulse wave velocity using mobile phone sensors | |
| RU2327414C1 (en) | Method of blood pressure measurement based on three-dimensional compression oscillogram | |
| TWI228981B (en) | System and method for measurement and analysis of pulses from finger |
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 |