CN107785081A - Calculate method, apparatus, storage medium and the equipment of central hemodynamics index - Google Patents

Abstract

The present invention provides a kind of method, apparatus, storage medium and equipment for calculating central hemodynamics index.Wherein calculate central hemodynamics and refer to calibration method, comprise the following steps：The radial artery pulse wave signal of collection is demarcated using the brachial arterial pressure of collection, obtains radial artery wave shape；According to the radial artery wave shape, central aortic waveform morphology is predicted using linear regression model (LRM)；According to the central aortic waveform morphology, the transmission function corresponding to selection between the radial artery wave shape and central aortic pressure wave shape, according to the transmission function, the radial artery pulse wave signal reconstruction central aortic pressure wave shape is utilized；Central hemodynamics index is calculated according to the central aortic pressure wave shape.Present invention only requires extraction radial artery pulse wave can to obtain the hemodynamic indexs such as central aortic pressure, and radial artery pulse wave is more stable and is easy to extract, and potential safety hazard is not present in human test.

Description

Method, device, storage medium and equipment for calculating central hemodynamics index

Technical Field

The invention relates to the technical field of biomedical engineering, in particular to a method and a device for calculating a central hemodynamic index, a computer readable storage medium, computer equipment and a computer program product.

Background

Central arterial pressure refers to the pressure of the central aortic root to the blood against the wall of a blood vessel per unit area. Studies have shown that central arterial pressure accurately reflects the loading conditions applied to the left ventricle, coronary arteries and cerebral vessels. In meta-analysis by Vlachopoulos et al, it was shown that the total cardiovascular event risk increased 8.8% for every 10mmHg increase in central arterial systolic pressure (SBP). Therefore, accurate measurement of central arterial pressure is of great significance for the prevention and treatment of cardiovascular diseases.

Methods for determining central arterial pressure are clinically classified into two types according to invasiveness: firstly, the aortic root blood pressure is directly measured by an invasive catheter method; and secondly, carrying out non-invasive estimation on the central arterial pressure through waveform analysis. The invasive catheter method is characterized in that one end of a liquid-filled catheter is sent to the root part of a central aorta through femoral artery or radial artery, the other end of the catheter is connected with a pressure sensor, and the pressure sensor records the pressure in the blood vessel in real time so as to accurately acquire the pressure wave of the aorta. The invasive catheter method is mainly used in the fields of first aid, intensive care unit and the like, and can be used as a 'gold standard' for evaluating the accuracy of the noninvasive method. However, the method has the disadvantages of invasiveness and risks, great operation difficulty and inapplicability to common patients and healthy people. The non-invasive estimation method mainly analyzes large sample data to construct a mathematical model between a central artery and a peripheral artery, namely a transfer function model. From the measured waveform of the human radial artery pressure, a central artery pressure waveform is obtained using the transfer function.

Karamanoglu et al constructed the transfer function from aorta to radial based on Fourier transform. The SphygmoCor CVSM noninvasive CAP assessment system developed by athcor medical corporation, australian, li, is currently the most widely and most approved Central Arterial Pressure (CAP) detection instrument in clinical application. The instrument is the only noninvasive CAP detection instrument which is certified by the FDA of the U.S. food and drug administration at present. The built-in Generalized Transfer Function (GTF) of the instrument is constructed based on a fourier transform method. However, the model does not take into account the influence factors of the transfer function, and the transfer function has a great influence on the accuracy of the calculation result.

Disclosure of Invention

It is an object of the present application to overcome the above problems or to at least partially solve or mitigate the above problems.

The invention provides a method for calculating a central hemodynamics index, which comprises the following steps:

calibrating the collected pulse wave signal of the radial artery by utilizing the collected blood pressure of the brachial artery to obtain a radial artery pressure waveform;

predicting the waveform form of the central artery by utilizing a linear regression model according to the radial artery pressure waveform;

selecting a transfer function between the corresponding radial artery pressure waveform and the central artery pressure waveform according to the central artery waveform form, and reconstructing the central artery pressure waveform by using the radial artery pulse wave signal according to the transfer function;

and calculating a central hemodynamic index according to the central arterial pressure waveform.

Preferably, the step of calibrating the acquired radial artery pulse wave signal by using the acquired brachial artery blood pressure to obtain a radial artery pressure waveform specifically includes:

for the collected radial pulse wave signals, removing the baseline drift of the radial pulse wave signals by filtering the noise of the radial pulse wave signals to obtain radial pulse wave waveforms;

and calibrating the radial artery pulse waveform by using the brachial artery blood pressure to obtain the radial artery pressure waveform.

Preferably, the step of predicting the central artery waveform morphology by using a linear regression model according to the radial artery pressure waveform specifically includes:

calculating a radial artery augmentation index according to the radial artery pressure waveform;

inputting the radial artery augmentation index and the age into the linear regression model to obtain a central artery augmentation index estimation value;

predicting the central artery waveform morphology using the central artery augmentation index estimate.

Preferably, wherein the transfer function is obtained as follows:

dividing the sample data into a plurality of groups according to the actual central artery waveform form of the sample data;

for each sample data in each group, constructing a personal transfer function between the radial artery pressure waveform and the actual central artery pressure waveform using fourier analysis;

and superposing and averaging the personal transfer functions to obtain a transfer function corresponding to the actual central artery waveform form.

Preferably, the selecting a transfer function between the corresponding radial artery pressure waveform and central artery pressure waveform according to the central artery waveform morphology, and the reconstructing a central artery pressure waveform by using the radial artery pulse wave signal according to the transfer function specifically includes:

selecting a transfer function between the corresponding radial artery pressure waveform and central artery pressure waveform according to the central artery waveform morphology;

transforming the radial pulse signal from a time domain to a frequency domain using a discrete time fourier transform;

respectively operating a plurality of first harmonic components of the radial artery pulse signal and harmonic components in the transfer function in a complex field;

and superposing the calculated harmonic components, and reconstructing to obtain the central artery pressure waveform.

Preferably, wherein the central hemodynamic index comprises one or more of the following: central arterial systolic pressure, central arterial diastolic pressure, central arterial pulse pressure, growth pressure, ejection time, reflected wave growth index, systolic pressure time integral, diastolic pressure time integral, and subendocardial myocardium activity rate.

The invention also provides a device for calculating the central hemodynamics index, which comprises the following modules:

the calibration module is configured to calibrate the acquired radial artery pulse wave signal by using the acquired brachial artery blood pressure to obtain a radial artery pressure waveform;

a prediction module configured to predict a central artery waveform morphology using a linear regression model from the radial artery pressure waveform of the calibration module;

the reconstruction module selects a transfer function between the corresponding radial artery pressure waveform and the central artery pressure waveform according to the central artery waveform form of the prediction module, and reconstructs the central artery pressure waveform by using the radial artery pulse wave signal according to the transfer function;

and the calculation module is used for calculating a central hemodynamic index according to the central arterial pressure waveform of the reconstruction module.

Preferably, the reconstruction module specifically includes:

a transfer function selection module configured to select a transfer function between the corresponding radial artery pressure waveform and central artery pressure waveform according to the central artery waveform morphology of the prediction module;

a frequency domain transformation module configured to transform the radial artery pulse signal from a time domain to a frequency domain using a discrete time fourier transform;

the harmonic component operation module is configured to respectively operate the first harmonic components of the radial artery pulse signals obtained by the frequency domain transformation module and the harmonic components in the transfer function selected by the transfer function selection module in a complex field;

and the superposition reconstruction module is configured to superpose the harmonic components after the operation of the harmonic component operation module, and reconstruct the central artery pressure waveform.

The invention also provides a computer-readable storage medium, in which a computer program is stored which, when being executed by a processor, carries out the method of calculating a central hemodynamic index as described above.

The invention also provides a computer device comprising a memory, a processor and a computer program stored in the memory and executable by the processor, wherein the processor, when executing the computer program, implements the method of calculating a central hemodynamic index as described above.

The invention optimizes the calculation method by adopting the transfer function model, thereby effectively improving the accuracy of the calculation result.

Furthermore, the collected brachial artery blood pressure is used for calibrating the collected radial artery pulse wave signals, so that the accuracy of subsequent results is improved.

Furthermore, a transfer function model is selected according to the waveform form of the central artery, so that different transfer functions can be selected according to different ages and constitutions, and the applicability and flexibility of the method are improved.

Furthermore, the linear regression model is adopted, the calculation amount is small, the calculation speed is high, and factors such as the radial artery pressure waveform, the actual central artery pressure waveform and the age are considered, so that the obtained linear regression model is more accurate.

Furthermore, the central artery pressure waveform is estimated by adopting a signal reconstruction mode, so that the method for non-invasively acquiring the central artery pressure waveform based on the radial artery pulse wave signal is realized, the data acquisition process is convenient and simple, and the time is saved.

Drawings

The above and other objects, advantages and features of the present application will become more apparent to those skilled in the art from the following detailed description of specific embodiments thereof, taken in conjunction with the accompanying drawings.

Some specific embodiments of the present application will be described in detail hereinafter by way of illustration and not limitation with reference to the accompanying drawings. The same reference numbers in the drawings identify the same or similar elements or components. Those skilled in the art will appreciate that the drawings are not necessarily drawn to scale. In the drawings:

FIG. 1 shows a flow chart of a method of calculating a central hemodynamic index of the present invention;

FIG. 2a shows a class A central artery waveform map;

FIG. 2b shows a class C central artery waveform map;

FIG. 3 shows a schematic diagram of a central artery hemodynamic related index;

fig. 4 shows a block diagram of an apparatus for calculating a central hemodynamic index of the present invention.

Detailed Description

The present invention will be described in detail below with reference to the accompanying drawings.

According to an aspect of the present invention, there is provided a method for calculating a central hemodynamic index, comprising the steps of:

1. calibrating the collected pulse wave signal of the radial artery by utilizing the collected blood pressure of the brachial artery to obtain a radial artery pressure waveform;

2. predicting the waveform form of the central artery by utilizing a linear regression model according to the radial artery pressure waveform;

3. selecting a transfer function between a corresponding radial artery pressure waveform and a central artery pressure waveform according to the waveform form of the central artery, and reconstructing the central artery pressure waveform by using a radial artery pulse wave signal according to the transfer function;

4. and calculating the central hemodynamic index according to the central arterial pressure waveform.

Preferably, step 1 may comprise the steps of:

1.1 for the collected radial artery pulse wave signals, removing the baseline drift of the radial artery pulse wave signals by filtering the noise of the radial artery pulse wave signals to obtain radial artery pulse wave waveforms;

1.2 calibrating the pulse waveform of the radial artery by using the blood pressure of the brachial artery to obtain the pressure waveform of the radial artery.

Specifically, the electronic sphygmomanometer can be used for acquiring brachial artery blood pressure of the human body, and the pulse signal sensor can be used for acquiring radial artery pulse waveforms of the human body.

The human brachial artery blood pressure can comprise brachial artery systolic pressure SBP and brachial artery diastolic pressure DBP, and brachial artery average pressure MAP can be calculated according to the brachial artery systolic pressure SBP and the brachial artery diastolic pressure DBP, and the calculation method of the brachial artery average pressure is MAP-DBP +0.4 (SBP-DBP).

Since various external noises greatly affect the radial pulse waveform during measurement, which is not beneficial to the analysis of subsequent signals and the calculation of indexes, the noises need to be filtered. The pulse waveform of the radial artery is generally a non-stationary non-periodic signal, more than 90% of the spectral energy is concentrated below 10Hz, and the interference components mainly comprise two types, namely high-frequency noise and baseline drift. For high frequency noise, one or more of the following filtering methods may be employed: wiener filtering, kalman filtering, FIR filtering, wavelet transformation, etc. The cut-off frequency of the filter can be selected to be 10 Hz. For baseline drift, morphological removal can be employed. And processing the acquired radial pulse wave signals to obtain radial pulse waveforms.

Then, the pulse waveform of the radial artery is calibrated by using the blood pressure of the brachial artery to obtain the pressure waveform of the radial artery. Since the acquired radial pulse waveform is dimensionless, it needs to be calibrated. The radial artery pressure waveform obtained by calibrating the radial artery pulse waveform by using the brachial artery blood pressure has blood pressure dimension with unit of mmHg, thereby obtaining the pressure waveform with physiological significance. For example, the radial pulse waveform can be calibrated using the brachial artery diastolic pressure DBP and the brachial artery mean pressure MAP. The calibration method comprises the following specific steps:

1.2.1 obtaining brachial artery diastolic pressure DBP and brachial artery average pressure MAP;

1.2.2 obtaining a radial pulse waveform p (t) of one period;

1.2.3 calculating the mean value p of the radial pulse waveform p (t)_meanAnd a minimum value p_min；

1.2.4 radial artery pressure waveform p (t) ═ DBP + (MAP-DBP) × (p (t) — p_min)/(p_mean-p_min)。

Preferably, the 2 nd step may include the steps of:

2.1 calculating radial artery augmentation index according to the radial artery pressure waveform;

2.2 inputting the radial artery augmentation index and the age into a linear regression model to obtain a central artery augmentation index estimation value;

2.3 central artery waveform morphology is predicted using central artery augmentation index estimates.

The construction of the linear regression model may include the following steps:

(1) radial artery pressure waveforms and actual central artery pressure waveforms and their age were obtained for m subjects. Preferably, the subjects are persons of the same nationality, e.g., both Chinese. Preferably, m is more than or equal to 200;

(2) and calculating a radial artery augmentation index rAIx according to the radial artery pressure waveform, and calculating a central artery augmentation index cAIx according to the actual central artery pressure waveform.

(3) And constructing a linear regression model according to the radial artery augmentation index rAIx, the age and the central artery augmentation index cAIx, and estimating by a least square method to obtain undetermined parameters of the regression model.

Wherein the linear regression model may take the form of equation (1):

wherein,estimating for linear regression analysis, namely central artery enhancement index estimation; a. b₁、b₂Undetermined parameters of the regression model; rAIx is the radial artery augmentation index. And (3) estimating the undetermined parameters of the regression model by using known data samples (cAIx, rAIx and age) of m subjects through a least square method, wherein an equation system for solving the undetermined parameters of the regression model is shown as a formula (2):

and after the undetermined parameters of the model are determined, completing the construction of the linear regression model.

When the method is applied, the radial artery augmentation index rAIx and the age of a measured person can be input into a regression model, and then the central artery augmentation index estimation value can be obtained. And predicting the central artery waveform morphology of the measured person according to the central artery enhancement index estimation value.

The central arterial waveform morphology of the human body can be divided using a variety of criteria. For example, classification may be based on the size of the central artery augmentation index cAIx. In a preferred embodiment, for example, the central artery waveform morphology may be classified into class a, class B, and class C. The standard of the division is that if the central artery enhancement index cAIx is larger than or equal to zero, the waveform form of the central artery of the person is A type or B type; if the central artery enhancement index cAIx is less than zero, the human central artery waveform is C-type.

Typical central artery waveform configurations are shown in fig. 2a and 2B, and as shown in fig. 2a, when the reflection points of the a-type waveform and the B-type waveform (where the B-type waveform is not shown) are located before the peak point, the central artery enhancement index cAIx is greater than or equal to zero; as shown in fig. 2b, the reflection point of the C-type waveform is located after the peak point, and the central artery enhancement index cAIx is less than zero. Therefore, the central artery waveform morphology can be judged according to the value of the central artery enhancement index cAIx.

It should be understood that other methods of constructing a regression model may be used, such as constructing a non-linear regression model. More parameters can be adopted to construct a linear regression model so as to estimate the waveform shape of the central artery. Other suitable criteria may be used to classify the morphology of the central artery waveform.

Preferably, the construction of the transfer function in step 3 may include the steps of:

(1) dividing the sample data into a plurality of groups according to the actual central artery waveform form of the sample data;

(2) for each sample data in each group, constructing a personal transfer function between a radial artery pressure waveform and an actual central artery pressure waveform by using a Fourier analysis method;

(3) and (4) superposing and averaging the individual transfer functions to obtain a transfer function corresponding to the actual central artery waveform form.

The steps (1) to (3) of constructing the transfer function may be specifically realized by the following procedures;

(1) sample data was acquired for n subjects, including a radial artery pressure waveform and an actual central artery pressure waveform.

In a preferred embodiment, first, a central artery waveform and a radial artery waveform of n subjects are acquired, and then the two-path waveforms are preprocessed, wherein the preprocessing includes filtering noise of pulse wave signals, removing baseline drift of the pulse wave signals, obtaining a radial artery pulse waveform, and calibrating the radial artery pulse waveform with brachial artery diastolic pressure DBP and brachial artery mean pressure MAP, so as to obtain an actual central artery pressure waveform and a radial artery pressure waveform.

Preferably, the subjects are persons of the same nationality, e.g., both Chinese. Preferably, n.gtoreq.200. Preferably, the actual central arterial pressure waveform is the subject's carotid pressure waveform.

And calculating a central artery enhancement index cAIx according to an actual central artery pressure waveform to further obtain a central artery waveform form, and dividing the sample data into a plurality of groups according to the central artery waveform form. For example, the subjects can be classified into a group a and a group C according to the size of the central artery augmentation index cAIx, and further, the central waveform morphology of the subjects in the group a is classified into a class a or B, and the central waveform morphology of the subjects in the group C is classified into a class C. Therefore, the sample data is divided into a plurality of groups according to the actual central artery waveform morphology of the sample data.

(2) Personal transfer functions between central and radial artery pressure waveforms were constructed in groups a and C, respectively. Wherein the transfer function between the central arterial pressure waveform and the radial arterial pressure waveform comprises a personal transfer function from the central arterial pressure waveform to the radial arterial pressure waveform and a personal transfer function from the radial arterial pressure waveform to the central arterial pressure waveform.

Taking the example of constructing the transfer function from the central artery pressure waveform to the radial artery pressure waveform, for each sample data in the group a and the group C, the discrete fourier transform is performed on the radial artery pressure waveform and the central artery pressure waveform in the sample data according to the formulas (3) and (4) respectively to obtain the frequency domain forms of the radial artery pressure waveform and the central artery pressure waveform.

In the formula, P_R(t) a time domain function representing the radial artery pressure waveform, P_C(t) represents the time domain function of the central arterial pressure waveform, DFT represents the discrete Fourier transform operation, F_R(ω) frequency domain function representing radial artery pressure waveform, F_C(ω) represents the frequency domain function of the central artery pressure waveform,andrespectively, in the form of complex domain expression of frequency domain function of radial artery pressure waveform and frequency domain function of cardiac pulse pressure waveform, wherein M_R(ω)、M_C(ω) andthe amplitude and phase of the radial artery pressure waveform and the cardiac pulse pressure waveform, respectively. Personal transfer function ITF from central arterial pressure waveform to radial arterial pressure waveform_C→RCan be defined as formula (5):

wherein M is_C→R(ω)＝M_R(ω)/M_C(ω) represents ITF_C→RThe amplitude of (d);indicating ITF_C→RThe phase of (c).

(3) The individual transfer functions from the central cardiac pulse pressure waveform to the radial artery pressure waveform in group a and group C are averaged separately to obtain two transfer functions that correspond to the actual central artery waveform morphology of group a and group C, respectively.

It will be appreciated that the above concept can also be followed to construct a personal transfer function from a radial artery pressure waveform to a central artery pressure waveform, such as equation (6), and thus construct a corresponding transfer function.

Wherein the meaning of each parameter is similar to equation (5).

Preferably, step 3 can be obtained as follows:

3.1 selecting a transfer function between the corresponding radial artery pressure waveform and the central artery pressure waveform according to the central artery waveform form;

3.2 transforming the radial pulse signal from the time domain to the frequency domain by using discrete time Fourier transform;

3.3 respectively operating the first multiple harmonic components of the radial artery pulse signal and the harmonic components in the transfer function in the complex field;

and 3.4, overlapping the harmonic components after operation, and reconstructing to obtain a central artery pressure waveform.

Specifically, the transfer function corresponding to the predicted central artery shape of the human body may be selected. And transforming the radial artery pulse signal from a time domain to a frequency domain by utilizing discrete time Fourier transform (DTF), and if a transfer function from the central artery pressure waveform to the radial artery pressure waveform is selected, dividing each harmonic component of the frequency domain of the radial artery pulse signal by a harmonic component corresponding to the transfer function in a complex domain to obtain the amplitude and the phase of the reconstructed central artery pressure waveform. Preferably, the first 10 harmonic components of the radial pulse signal may be taken, and the 10 harmonic components are divided by the first 10 components in the complex domain of the transfer function from the central artery pressure waveform to the radial artery pressure waveform, respectively. The central arterial pressure waveform y is reconstructed by the following equation (7)_est。

Wherein, preferably, N is 10, 1. ltoreq. n.ltoreq.10, A₀The direct component of the central arterial pressure waveform (signal mean). A. the_nAndthe amplitude and phase, respectively, of the nth harmonic of the central arterial pressure waveform.

It can be understood that, if a transfer function from the radial artery pressure waveform to the central artery pressure waveform is adopted, each harmonic component of the complex field of the radial artery pulse signal is multiplied by the corresponding harmonic component of the transfer function in the complex field.

Preferably, the 4 th step can be obtained as follows:

from the reconstructed central arterial pressure waveform, one or more of the following central hemodynamic indices may be calculated: central aortic systolic pressure cbbp, central arterial diastolic pressure cDBP, central arterial pulse pressure cPP, increase pressure AP, ejection time Ed, reflected wave increase index AIx, systolic pressure time integral SPTI, diastolic pressure time integral DPTI, and subendocardial myocardium viability rate SEVR.

Specifically, as shown in fig. 3, the cSBP is the central aortic systolic pressure, corresponding to the peak point of the waveform. cDBP is central arterial diastolic pressure, corresponding to the wave trough point of the waveform. cPP is central arterial pulse pressure, and its calculation formula is cPP ═ cSBP-cDBP. AP is the increase in pressure corresponding to the increase in blood pressure from the first shoulder point to the peak point. AIx is a reflection wave growth index, and the calculation formula is AIx ═ AP/cPP. Ed is the ejection time, corresponding to the duration of the systolic phase of the pressure waveform. The SPTI is the systolic pressure time integral, corresponding to the area of the region encompassed by the systolic pressure waveform. DPTI is the diastolic pressure time integral, corresponding to the area of the region encompassed by the diastolic pressure waveform. Subendocardial myocardial viability rate SEVR is the ratio of SPTI to DPTI.

According to another aspect of the present invention, there is provided an apparatus for calculating a central hemodynamic index, comprising the following modules, as shown in fig. 4:

1. the calibration module is configured to calibrate the acquired radial artery pulse wave signal by using the acquired brachial artery blood pressure to obtain a radial artery pressure waveform;

2. the prediction module is configured to predict the waveform form of the central artery by utilizing a linear regression model according to the radial artery pressure waveform of the calibration module;

3. a reconstruction module configured to reconstruct a central artery pressure waveform based on the radial artery pulse wave signal according to a central artery waveform morphology of the prediction module using a transfer function between a corresponding radial artery pressure waveform and the central artery pressure waveform;

4. a calculation module configured to calculate a central hemodynamic index from the central arterial pressure waveform of the reconstruction module.

Preferably, the calibration module may comprise the following modules:

1.1 a radial pulse wave signal processing module configured to filter noise of the radial pulse wave signal and remove baseline drift of the radial pulse wave signal to obtain a radial pulse wave waveform for the acquired radial pulse wave signal;

1.2 a radial artery pressure waveform generating module configured to calibrate a radial artery pulse waveform of the radial artery pulse wave signal processing module by means of brachial artery blood pressure to obtain a radial artery pressure waveform. Preferably, wherein the brachial arterial blood pressure comprises brachial arterial systolic pressure and brachial arterial diastolic pressure.

Preferably, the prediction module may comprise the following modules:

2.1 a radial artery augmentation index calculation module configured to calculate a radial artery augmentation index from the radial artery pressure waveform of the calibration module;

2.2 an estimation module configured to input the radial artery augmentation index of the age and radial artery augmentation index calculation module into a linear regression model to obtain a central artery augmentation index estimation value;

2.3 a prediction module configured to predict a central artery waveform morphology using the central artery enhancement index estimate of the estimation module.

Preferably, the apparatus for calculating a central hemodynamic index may further include a linear regression model building module, and the linear regression model building module may include the following modules:

(1) a data acquisition module configured to acquire radial artery pressure waveforms and actual central artery pressure waveforms of a number of subjects and their ages;

(2) the calculation module is configured to calculate a radial artery augmentation index rAIx according to the radial artery pressure waveform of the data acquisition module, and calculate a central artery augmentation index cAIx according to the actual central artery pressure waveform;

(3) and the model and parameter determining module is configured to construct a linear regression model according to the radial artery enhancement index rAIx and the central artery enhancement index cAIx of the calculating module and the age acquired by the data acquiring module, and estimate to-be-determined parameters of the regression model by a least square method.

Preferably, the apparatus for calculating a central hemodynamic index may further include a transfer function construction module, and the transfer function construction module may include the following modules:

(1) a grouping module configured to group the sample data into a number of groups according to an actual central artery waveform morphology;

(2) a personal transfer function generation module configured to construct a personal transfer function from a radial artery pressure waveform to an actual central artery pressure waveform using fourier analysis for each sample data in each group of the grouping module;

(3) and the transfer function generating module is configured to superpose and average the personal transfer functions of each group generated by the personal transfer function generating module to obtain a transfer function corresponding to the actual central artery waveform form.

Preferably, the reconstruction module may include the following modules:

3.1 a transfer function selection module configured to select a transfer function between a corresponding radial artery pressure waveform and a central artery pressure waveform according to a central artery waveform morphology of the prediction module;

3.2 a frequency domain transformation module configured to transform the radial pulse signal from the time domain to the frequency domain using a discrete time fourier transform;

3.3 harmonic component operation module, configured to separately operate the first several harmonic components of the radial artery pulse signal obtained by the frequency domain transformation module and the harmonic components in the transfer function selected by the transfer function selection module in the complex number domain;

and 3.4 a superposition reconstruction module configured to superpose the harmonic components after the operation of the harmonic component operation module, and reconstruct the harmonic components to obtain the central artery pressure waveform.

Preferably, the calculation module may calculate one or more of the following central artery hemodynamic indices from the central artery pressure waveform of the reconstruction module:

central aortic systolic pressure cbbp, central arterial diastolic pressure cDBP, central arterial pulse pressure cPP, increase pressure AP, ejection time Ed, reflected wave increase index AIx, systolic pressure time integral SPTI, diastolic pressure time integral DPTI, and subendocardial myocardium viability rate SEVR.

According to another aspect of the invention, a computer-readable storage medium is provided, in which a computer program is stored which, when being executed by a processor, carries out the above-mentioned method of calculating a central hemodynamic index.

According to another aspect of the invention, a computer device is provided, comprising a memory, a processor and a computer program stored in the memory and executable by the processor, wherein the processor when executing the computer program implements the method of calculating a central hemodynamic index as described above.

According to another aspect of the invention, a computer program product is provided, comprising computer readable code which, when executed by a computer device, causes the computer device to perform the above method of calculating a central hemodynamic index.

The invention corrects the traditional transfer function model and effectively improves the applicability of the transfer function model. Compared with the prior art, the technical scheme adopted by the invention has the advantages that the beneficial effects comprise but are not limited to the following aspects:

(1) the invention constructs the transfer function with a specific form according to the central artery waveform form, and can effectively improve the precision of the transfer function.

(2) The invention constructs a linear regression model to predict the waveform form of the central artery of the human body, and further selects a transfer function model with a proper form, so that the reconstructed central artery waveform is more accurate.

(3) The invention can obtain the hemodynamic indexes such as central arterial pressure and the like only by extracting the radial pulse wave, the radial pulse wave is more stable and easy to extract, and the potential safety hazard does not exist during the human body test.

The present invention has been described in detail with reference to the accompanying drawings, but it should be understood by those skilled in the art that the description is only for the purpose of explaining the claims. The scope of the invention is not limited by the description. Any changes or substitutions that can be easily made by those skilled in the art within the technical scope of the disclosure of the present invention should be covered within the protective scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.

Claims (10)

1. A method for calculating a central hemodynamic index, comprising the steps of:

calibrating the collected pulse wave signal of the radial artery by utilizing the collected blood pressure of the brachial artery to obtain a radial artery pressure waveform;

predicting the waveform form of the central artery by utilizing a linear regression model according to the radial artery pressure waveform;

selecting a transfer function between the corresponding radial artery pressure waveform and the central artery pressure waveform according to the central artery waveform form, and reconstructing the central artery pressure waveform by using the radial artery pulse wave signal according to the transfer function;

and calculating a central hemodynamic index according to the central arterial pressure waveform.

2. The method of calculating a central hemodynamic index of claim 1, wherein the step of calibrating the collected pulse wave signal of the radial artery with the collected brachial artery blood pressure to obtain a waveform of the radial artery pressure specifically comprises:

for the collected radial pulse wave signals, removing the baseline drift of the radial pulse wave signals by filtering the noise of the radial pulse wave signals to obtain radial pulse wave waveforms;

and calibrating the radial artery pulse waveform by using the brachial artery blood pressure to obtain the radial artery pressure waveform.

3. The method according to claim 1, wherein the step of predicting the morphology of the central artery waveform from the radial artery pressure waveform using a linear regression model comprises:

calculating a radial artery augmentation index according to the radial artery pressure waveform;

inputting the radial artery augmentation index and the age into the linear regression model to obtain a central artery augmentation index estimation value;

predicting the central artery waveform morphology using the central artery augmentation index estimate.

4. A method of calculating a central hemodynamic index as recited in claim 1, wherein said transfer function is obtained by:

dividing the sample data into a plurality of groups according to the actual central artery waveform form of the sample data;

for each sample data in each group, constructing a personal transfer function between the radial artery pressure waveform and the actual central artery pressure waveform using fourier analysis;

and superposing and averaging the personal transfer functions to obtain a transfer function corresponding to the actual central artery waveform form.

5. The method of calculating a central hemodynamic index of claim 1, wherein the step of selecting a transfer function between the corresponding radial artery pressure waveform and central artery pressure waveform according to the central artery waveform morphology, and reconstructing a central artery pressure waveform from the radial artery pulse wave signal according to the transfer function specifically comprises:

selecting a transfer function between the corresponding radial artery pressure waveform and central artery pressure waveform according to the central artery waveform morphology;

transforming the radial pulse signal from a time domain to a frequency domain using a discrete time fourier transform;

respectively operating a plurality of first harmonic components of the radial artery pulse signal and harmonic components in the transfer function in a complex field;

and superposing the calculated harmonic components, and reconstructing to obtain the central artery pressure waveform.

6. The method of calculating a central hemodynamic index of any of claims 1 to 5, wherein the central hemodynamic index comprises one or more of: central arterial systolic pressure, central arterial diastolic pressure, central arterial pulse pressure, growth pressure, ejection time, reflected wave growth index, systolic pressure time integral, diastolic pressure time integral, and subendocardial myocardium activity rate.

7. An apparatus for calculating a central hemodynamic index, comprising:

the calibration module is configured to calibrate the acquired radial artery pulse wave signal by using the acquired brachial artery blood pressure to obtain a radial artery pressure waveform;

a prediction module configured to predict a central artery waveform morphology using a linear regression model from the radial artery pressure waveform of the calibration module;

the reconstruction module selects a transfer function between the corresponding radial artery pressure waveform and the central artery pressure waveform according to the central artery waveform form of the prediction module, and reconstructs the central artery pressure waveform by using the radial artery pulse wave signal according to the transfer function;

and the calculation module is used for calculating a central hemodynamic index according to the central arterial pressure waveform of the reconstruction module.

8. The apparatus for calculating a central hemodynamic index of claim 7, wherein the reconstruction module comprises:

a transfer function selection module configured to select a transfer function between the corresponding radial artery pressure waveform and central artery pressure waveform according to the central artery waveform morphology of the prediction module;

a frequency domain transformation module configured to transform the radial artery pulse signal from a time domain to a frequency domain using a discrete time fourier transform;

the harmonic component operation module is configured to respectively operate the first harmonic components of the radial artery pulse signals obtained by the frequency domain transformation module and the harmonic components in the transfer function selected by the transfer function selection module in a complex field;

and the superposition reconstruction module is configured to superpose the harmonic components after the operation of the harmonic component operation module, and reconstruct the central artery pressure waveform.

9. A computer-readable storage medium, in which a computer program is stored which, when being executed by a processor, carries out the method of calculating a central hemodynamic index of any one of claims 1 to 6.

10. A computer device comprising a memory, a processor and a computer program stored in the memory and executable by the processor, wherein the processor when executing the computer program implements a method of calculating a central hemodynamic index as claimed in any of claims 1 to 6.