Model-driven arterial blood flow dynamics measurement method and device, equipment and computer readable storage medium

Abstract

The application discloses a model-driven arterial hemodynamics measurement method and device, equipment and a computer readable storage medium, and the method comprises the following steps: collecting arterial blood pressure waveform time series data in a preset cardiac cycle; inputting the arterial blood pressure waveform time series data into a preset aortic hemodynamics coupling model to obtain aortic hemodynamics waveform characteristic parameters; and determining cardiac output according to the aortic hemodynamics waveform characteristic parameters; wherein the preset aortic hemodynamics coupling model is formed by coupling a one-dimensional blood flow dynamics model simulating aortic blood vessel transmission characteristics and a zero-dimensional multi-elastic cavity model simulating peripheral arterial circulation impedance characteristics. The one-dimensional model in the coupling model can accurately depict the blood flow in the aorta and the pulse wave propagation and reflection phenomenon, and realize high-precision solution of blood pressure, flow velocity and flow waveform; the zero-dimensional model simulates the blood flow process of the peripheral artery and serves as a boundary condition of the one-dimensional model, so that the overall blood flow simulation is more in line with the real physiological state.

Description

Technical Field

[0001] This application relates to the field of blood flow measurement technology, and in particular to a model-driven method, apparatus, device and computer-readable storage medium for measuring arterial hemodynamics. Background Technology

[0002] Currently, most mainstream arterial blood flow measurement techniques employ a single flow calculation model. These techniques typically simplify the complex cardiovascular system as simple electrical components for modeling, resulting in a rudimentary model that fails to accurately simulate the actual propagation path and reflection of pulse waves within the vascular network. This leads to significant deviations in the calculated blood flow waveform, failing to meet the demands for high-precision detection.

[0003] Meanwhile, existing measurement schemes mostly rely on publicly available statistical data and traditional empirical formulas to assign values ​​to key model parameters, failing to establish an individualized parameter system based on the actual physiological characteristics of the subjects. The standardized, universal parameter configurations differ significantly from the actual physiological states of different patients, easily introducing inherent calculation errors and further reducing the accuracy and clinical reference value of the overall arterial blood flow measurement results, thus hindering accurate clinical assessment of hemodynamic status. Summary of the Invention

[0004] In view of the shortcomings of the prior art described above, the purpose of this application is to provide a model-driven method, device, equipment and computer-readable storage medium for measuring arterial hemodynamics, so as to solve the problems that the existing arterial blood flow measurement model is simple in modeling, it is difficult to accurately reproduce the pulse wave propagation and reflection characteristics, resulting in large deviations in the actual blood flow waveform measurement. At the same time, the key parameters of the model adopt a general fixed configuration, which cannot be adapted to the physiological characteristics of different subjects, thus reducing the accuracy of individualized blood flow measurement.

[0005] The first aspect of this application proposes a model-driven method for measuring arterial hemodynamics, comprising: Collect time-series data of arterial blood pressure waveform within a preset cardiac cycle, and input the time-series data of arterial blood pressure waveform into a preset aortic hemodynamic coupling model to obtain aortic hemodynamic waveform characteristic parameters; Cardiac output is determined based on the aforementioned aortic hemodynamic waveform characteristic parameters; The preset aortic hemodynamic coupling model is formed by coupling a one-dimensional hemodynamic model that simulates the aortic blood vessel transmission characteristics with a zero-dimensional multi-element elastic cavity model that simulates the peripheral arterial circulation impedance characteristics.

[0006] In some embodiments of this application, the formula for calculating the aortic stiffness parameter in the preset aortic hemodynamic coupling model is as follows:

[0007] in K A parameter representing the stiffness of the aorta. Indicates blood density, This indicates the carotid-femoral artery pulse wave velocity.

[0008] In some embodiments of this application, the formula for calculating peripheral arterial resistance in the preset aortic hemodynamic coupling model is as follows:

[0009]

[0010] in, Indicates peripheral systemic arterial resistance. Indicates the reference center output quantity. Indicates mean arterial pressure. This indicates capillary blood pressure. Indicates brachial artery diastolic pressure. This indicates the systolic blood pressure of the brachial artery.

[0011] In some embodiments of this application, the formula for calculating peripheral systemic artery compliance in the preset aortic hemodynamic coupling model is as follows:

[0012] in, Indicates peripheral systemic arterial compliance. This indicates the reference to the total arterial compliance of a normal adult human body. This indicates the subject's weight. Indicates standard reference weight. Indicates the carotid-femoral pulse wave velocity. Indicates blood density, Indicates the length of the aorta. This represents the diameter of the aorta at the axial coordinate x.

[0013] In some embodiments of this application, the formula for calculating the length of the aorta in the preset aortic hemodynamic coupling model is as follows: or

[0014] in, Indicates the length of the aorta. Indicates the height of male subjects. This indicates the height of the female test subjects.

[0015] In some embodiments of this application, the peripheral systemic arterial resistance in the preset aortic hemodynamic coupling model is adaptively corrected using the stroke volume measured by a preset non-invasive measurement method.

[0016] In some embodiments of this application, the arterial blood pressure waveform time-series data is collected using a non-invasive blood pressure monitor.

[0017] In some embodiments of this application, the arterial blood pressure waveform timing data is the aortic blood pressure waveform timing data.

[0018] A second aspect of this application provides a model-driven arterial hemodynamics measurement device, including a waveform parameter acquisition module and a cardiac output acquisition module; The waveform parameter acquisition module is used to collect arterial blood pressure waveform time-series data within a preset cardiac cycle, and input the arterial blood pressure waveform time-series data into a preset aortic hemodynamic coupling model to obtain aortic hemodynamic waveform characteristic parameters. The cardiac output acquisition module is used to determine the cardiac output based on the aortic hemodynamic waveform characteristic parameters. The preset aortic hemodynamic coupling model is formed by coupling a one-dimensional hemodynamic model that simulates the aortic blood vessel transmission characteristics with a zero-dimensional multi-element elastic cavity model that simulates the peripheral arterial circulation impedance characteristics.

[0019] A third aspect of this application provides an apparatus comprising: at least one processor, a memory, and a computer program stored in the memory and executable on the at least one processor, wherein the processor executes the computer program to implement the method described above.

[0020] A fourth aspect of this application provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the method described above.

[0021] Compared with the prior art, one or more embodiments of the above solutions may have the following advantages or beneficial effects: This application proposes a model-driven method for measuring arterial hemodynamics. A one-dimensional hemodynamic model simulates aortic blood flow, while a zero-dimensional multi-element elastic cavity model characterizes peripheral vascular resistance, compliance, and microcirculation perfusion characteristics, accurately reproducing peripheral blood flow impedance and buffering effects. This constructs a coupled one-dimensional and zero-dimensional aortic hemodynamic model. The one-dimensional model accurately depicts blood flow within the aorta and pulse wave propagation and reflection, enabling high-precision solutions for blood pressure, flow velocity, and flow rate waveforms. The zero-dimensional model simulates peripheral arterial blood flow and serves as the boundary condition for the one-dimensional model, making the overall blood flow simulation more closely resemble real physiological conditions. Simultaneously, non-invasive data is used for individualized calibration of model parameters, further improving the overall accuracy of hemodynamic measurements.

[0022] Other features and advantages of the invention will be set forth in the description which follows, and will be apparent in part from the description, or may be learned by practicing the invention. The objects and other advantages of the invention may be realized and obtained by means of the structures particularly pointed out in the description, claims, and drawings. Attached Figure Description

[0023] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the description of the embodiments of the present invention will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0024] Figure 1 The diagram shown is a schematic flowchart of the model-driven arterial hemodynamic measurement method described in the embodiments of this application.

[0025] Figure 2 The diagram shows the execution process of the model-driven arterial hemodynamic measurement method described in the embodiments of this application.

[0026] Figure 3 The diagram shown is a schematic representation of the structure of the preset aortic hemodynamic coupling model in the model-driven arterial hemodynamic measurement method described in the embodiments of this application.

[0027] Figure 4 The diagram shown is a schematic representation of the model-driven arterial hemodynamics measurement device described in the embodiments of this application.

[0028] Figure 5 The diagram shown is a structural schematic of the device described in an embodiment of this application.

[0029] Specific element symbols: 1-Model-driven arterial hemodynamic measurement device, 11-Waveform parameter acquisition module, 12-Cardiac output acquisition module, 2-Equipment, 20-Processor, 21-Memory, 22-Computer program. Detailed Implementation

[0030] To make the technical problems, technical solutions, and beneficial effects to be solved by this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and are not intended to limit the scope of this application.

[0031] It should be noted that when a component is referred to as being "set on" another component, it can be directly on or indirectly on that other component. When a component is referred to as being "connected to" another component, it can be directly connected to or indirectly connected to that other component.

[0032] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of this application, "multiple" means two or more, unless otherwise explicitly specified.

[0033] Current mainstream arterial blood flow measurement technologies mostly employ a single calculation model, simplifying the complex cardiovascular system into an equivalent model. This fails to accurately simulate pulse wave propagation and reflection, resulting in significant deviations in blood flow waveform calculations. Furthermore, the parameters in these models often rely on literature data and traditional experience, without being customized to the physiological characteristics of the subjects. These generic parameters are prone to calculation errors, significantly reducing measurement accuracy and clinical reference value, making it difficult to meet the demands of high-precision hemodynamic assessment. Additionally, current arterial blood flow measurement models often employ invasive calibration methods such as transpulmonary thermodilution (TPTD). For example, TPTD requires central venous puncture and femoral artery catheterization, which are invasive procedures prone to complications such as catheter-related bloodstream infections. This limits its application to monitoring only a small number of critically ill patients and makes it difficult to promote its use in general wards and outpatient settings.

[0034] Based on this, this application improves the model-driven arterial hemodynamic measurement methods, devices, equipment, and computer-readable storage media in the related technologies.

[0035] The model-driven arterial hemodynamic monitoring method proposed in this application can be widely applied in intensive care units (ICUs), coronary care units (CCUs), and operating rooms to provide real-time, non-invasive, and continuous dynamic monitoring of cardiac output (CO), stroke volume (SV), and aortic blood pressure for critically ill patients and those undergoing major surgeries. This allows for precise guidance in the infusion of anesthetic drugs, the rational use of vasoactive agents, and goal-directed fluid therapy. It can effectively replace traditional invasive monitoring methods such as pulse-indicated continuous cardiac output (PiCCO) monitoring and pulmonary artery catheterization (Swan-Ganz) catheters. Furthermore, it can be used for routine hemodynamic assessment of patients with various cardiovascular diseases, including hypertension, heart failure, and aortic stenosis, assisting clinicians in developing individualized antihypertensive regimens and standardized treatment plans for heart failure. Furthermore, the method described in this application can also be applied to cardiopulmonary rehabilitation centers and professional sports training fields, enabling non-invasive real-time monitoring of hemodynamic indicators during exercise to accurately assess the body's cardiac pumping reserve capacity, thereby developing scientific and reasonable sports rehabilitation and physical training programs.

[0036] Meanwhile, the algorithm model upon which this invention is based can be used as a core software module and integrated into wearable medical devices such as next-generation non-invasive continuous blood pressure monitoring devices, high-end medical-grade smartwatches, and smart rings, to achieve long-term, uninterrupted dynamic monitoring of the cardiovascular health status of the human body in out-of-hospital settings.

[0037] refer to Figure 1 As shown in the figure, the model-driven arterial hemodynamic measurement method of this application includes the following steps.

[0038] Step S101: Collect arterial blood pressure waveform time-series data within a preset cardiac cycle, input the arterial blood pressure waveform time-series data into a preset aortic hemodynamic coupling model, and obtain aortic hemodynamic waveform characteristic parameters.

[0039] A dynamic non-invasive pulse-time blood pressure monitor can be used to continuously collect the subject's arterial blood pressure waveform time-series data. The data is transmitted over a preset cardiac cycle, with each cycle sending the arterial blood pressure waveform time-series data within that cycle to a preset aortic hemodynamic coupling model. Simultaneously, the device can also collect the subject's arterial blood pressure waveform time-series data in real time and transmit it to the preset aortic hemodynamic coupling model, allowing the model to output the corresponding aortic hemodynamic waveform characteristic parameters in real time.

[0040] Further, the aortic hemodynamic coupling model is preset to be obtained by coupling a one-dimensional hemodynamic model simulating the transmission characteristics of aortic blood vessels and a zero-dimensional multi-element Windkessel model simulating the impedance characteristics of peripheral arterial circulation.

[0041] Step S102, determining cardiac output according to aortic hemodynamic waveform characteristic parameters.

[0042] Specifically, time integration can be performed on the aortic hemodynamic waveform characteristic parameters to obtain stroke volume; then cardiac output is calculated and obtained based on stroke volume in combination with heart rate.

[0043] In the model-driven arterial hemodynamic measurement method of this embodiment, the one-dimensional hemodynamic model is used to reproduce the aortic blood flow operation process, and the zero-dimensional multi-parameter Windkessel model is combined to characterize peripheral vascular resistance, vascular compliance and microcirculation perfusion characteristics, so as to accurately restore distal blood flow resistance and blood flow buffering effect, and then construct an aortic hemodynamic coupling model combining one-dimensional and zero-dimensional models. The one-dimensional model can accurately describe the dynamic changes of blood flow in the aorta, clarify the propagation and reflection mechanism of pulse waves, and complete high-precision calculation of blood pressure, blood flow velocity and flow waveforms; the zero-dimensional model supplements and improves the peripheral blood flow boundary constraints, effectively improving the consistency between the overall blood flow simulation results and the actual physiological state.

[0044] Reference Figure 2 as shown, steps S101 to S102 of the model-driven arterial hemodynamic measurement method of this embodiment are described in detail below.

[0045] Step S101, collecting arterial blood pressure waveform time-series data within a preset cardiac cycle, and inputting the arterial blood pressure waveform time-series data into the preset aortic hemodynamic coupling model to obtain aortic hemodynamic waveform characteristic parameters.

[0046] Specifically, the inflatable finger cuff matched with a dynamic non-invasive beat-to-beat sphygmomanometer can be worn on the subject's finger to obtain the arterial blood pressure waveform time-series data output by the dynamic non-invasive beat-to-beat sphygmomanometer P(t) , wherein the dynamic non-invasive beat-to-beat sphygmomanometer obtains the arterial blood pressure waveform time-series data based on the subject's finger blood pressure waveform collected by the inflatable finger cuff P(t) , at this time the arterial blood pressure waveform time-series data P(t) may be aortic blood pressure waveform time-series data, or finger blood pressure may be reconstructed into brachial artery blood pressure or aortic blood pressure as aortic blood pressure waveform time-series data. Other types of non-invasive sphygmomanometers or other matched devices can also be used to collect and obtain arterial blood pressure waveform time-series data P(t) , and the present application does not impose a fixed limitation thereon herein.

[0047] Then, the collected arterial blood pressure waveform time-series data within the preset cardiac cycle P(t)This data serves as input to a preset aortic hemodynamic coupling model. Multiple cardiac cycle durations can be set as preset cardiac cycles based on requirements, or a single cardiac cycle duration can be selected. Real-time acquired arterial blood pressure waveform time-series data can also be used as the arterial blood pressure waveform time-series data within the preset cardiac cycle. P(t) This application does not impose any fixed restrictions on it.

[0048] The pre-defined aortic hemodynamic coupling model in this application is composed of a one-dimensional hemodynamic model and a zero-dimensional multi-element elastic cavity model. The one-dimensional hemodynamic model is used to simulate the aortic vascular transmission characteristics, that is, to simulate the blood flow process in the aorta using the one-dimensional hemodynamic model; the zero-dimensional multi-element elastic cavity model is used to simulate the peripheral arterial circulatory impedance characteristics, that is, to simulate the blood flow process in the peripheral arteries of the aorta using the zero-dimensional multi-element elastic cavity model.

[0049] A one-dimensional hemodynamic model can accurately simulate the blood flow process within the aorta and the propagation and reflection of pulse waves in the aorta. Its governing equations are: (1) in, t For time, x The axial coordinates are along the centerline of the aorta. A The cross-sectional area of ​​the blood vessel. U The average axial flow velocity is the cross-sectional velocity of the blood vessel. P The average blood pressure across the cross-section of the blood vessel. ξ The coefficient of viscous friction is... μ For blood viscosity, ρ Blood density, K The stiffness parameter of the aorta. P 0 is the reference pressure. A 0 represents pressure. P The cross-sectional area of ​​the blood vessel at 0 is the reference cross-sectional area.

[0050] In one embodiment of this application, the reference cross-sectional area in the above-described one-dimensional hemodynamic model A 0 can be obtained using the following formula (2), and the expression of formula (2) is: (2) in Diastolic diameter of the proximal aorta. The diastolic diameter of the distal aorta. The length of the aorta, and the aforementioned diastolic diameter of the proximal aorta. and diastolic diameter of the distal aorta The length of the aorta can be obtained by measuring the length of the aorta in a subject using echocardiography. It can be obtained through the following formula (3), the expression of formula (3) is: or (3) in, Indicates the height of male subjects. The height of female subjects is indicated, and the unit of height for both types of subjects is centimeters. Furthermore, this application can obtain the length of the aorta based on the gender of the subject. This makes the length parameter of the aorta closer to the actual length of the subject's aorta, thus improving the accuracy of the aortic hemodynamic waveform characteristic parameters output by the coupled model. The two coefficients in equation (3) (i.e., 3.36 and 3.29) are values ​​obtained based on a large amount of experimental data.

[0051] In one embodiment of this application, the aortic stiffness parameter in the above-described one-dimensional hemodynamic model K It can be obtained using the following formula (4), and the expression of formula (4) is: (4) in Indicates blood density, This indicates the carotid-femoral artery pulse wave velocity. Specifically, the carotid-femoral artery pulse wave velocity... Blood density needs to be measured while the subject is in a supine position. 1060 kg / m 3 .

[0052] In one embodiment of this application, the reference pressure in the above-described one-dimensional hemodynamic model P 0 is set as brachial artery diastolic pressure. DBP Brachial artery diastolic pressure DBP This can be obtained by measuring the subject's blood pressure, including the brachial artery systolic pressure. SBP .

[0053] Further one-dimensional hemodynamic model of blood vessel cross-sectional area A The initial value can be set to the pressure. P Blood vessel cross-sectional area at 0 A 0 is equivalent to the average axial velocity of the blood vessel cross section. U The initial value is set to zero, and the average blood pressure in the cross-section of the blood vessel is... P The initial value is set equal to the reference pressure. P 0, coefficient of viscous friction ξ Set to 22.0, blood viscosity μ Set to 0.0035 blood density ρ Set to 1060 kg / m3 It should be noted that the above parameters can also be set to other reasonable values, and no fixed restrictions are imposed on them here.

[0054] The zero-dimensional multi-element elastic cavity model can be either a zero-dimensional ternary Windkessel model or a zero-dimensional quaternary Windkessel model. When the zero-dimensional ternary Windkessel model is selected, its governing equations are: (5) in P art Systemic arterial blood pressure, P cap Peripheral capillary blood pressure, Q ao It is the blood flow at the distal aorta (i.e., the blood flow at the last node d in the one-dimensional hemodynamic model at a given time step). Q art For systemic arterial blood flow, R art Peripheral systemic arterial resistance, C art For systemic arterial compliance.

[0055] Since total blood volume in the human body is highly positively correlated with body weight (approximately 70 mL / kg on average for adults), and total system compliance is proportional to total system volume, compliance at a specific body weight can be extrapolated from the compliance of a standard reference human body. In one embodiment of this application, the peripheral systemic artery compliance in a zero-dimensional ternary Windkessel model... It can be obtained using the following formula (7), and the expression of formula (7) is: (7) in, For reference, the total arterial compliance of a normal adult is usually taken as 1.5 mL / mmHg. The subject's weight (which can be obtained through measurement). This is the standard reference weight (usually 70 kg). Indicates the length of the aorta. This is the diameter at the aortic axial coordinate x. The subject's body surface area (BSA) can also be used to more accurately scale equation (8): (8) in, , Ht The subject's height (when the subject is male) When the subject is female, ) Wt For the subject's weight ， The standard reference surface area (usually taken as 1.8 m²) 2 ).

[0056] In one embodiment of this application, peripheral systemic arterial resistance in a zero-dimensional ternary Windkessel model The initial value can be obtained through the following formula (9), and the expression of formula (9) is: (9) in, Peripheral systemic arterial resistance, As the reference center output, Mean arterial pressure, For capillary blood pressure, This refers to the diastolic pressure of the brachial artery. This refers to the systolic blood pressure of the brachial artery.

[0057] Further reference center output The diastolic pressure of the brachial artery can be obtained by measuring the subject's blood pressure using echocardiography. and brachial artery systolic blood pressure It can be obtained by having the subject lie supine; it is assumed that blood flow in the peripheral capillaries is non-pulsatile, i.e., capillary blood pressure. P cap It is a constant, as assumed here. P cap =33mmHg.

[0058] Therefore, as can be seen from the above, when using the method of this application, in addition to the above-mentioned fixed numerical parameter settings, it is also necessary to measure the height of the subject beforehand. Ht and weight Wt Carotid-femoral pulse wave velocity in subjects in the supine position and brachial artery systolic blood pressure SBP and brachial artery diastolic pressure DBP Simultaneously, echocardiography was used to measure the baseline cardiac output of the subjects. And measure the diastolic diameter of the proximal aorta. D p and diastolic diameter of the distal aorta D d The diameter of the aorta at other locations can be determined based on the diastolic diameter of the proximal aorta. D p and diastolic diameter of the distal aorta D dInterpolation calculations are performed to obtain the parameters. Through the above measurements, precise definitions of individualized physiological parameters for the subject can be achieved. This setting enables the individualized, high-precision solution of aortic hemodynamic waveform characteristic parameters, addressing the current problem that arterial blood flow detection processes fail to establish an individualized parameter system based on the actual physiological characteristics of the subject, thus reducing the accuracy and clinical reference value of overall arterial blood flow measurement results and hindering accurate clinical assessment of hemodynamic status.

[0059] Acquire arterial blood pressure waveform time-series data for a preset cardiac cycle. P(t) After setting the parameters in the preset aortic hemodynamic coupling model, the time-series data of arterial blood pressure waveforms can be processed. P(t) The data is input into a preset aortic hemodynamic coupling model, which then outputs the corresponding aortic hemodynamic waveform characteristic parameters. Specifically, these parameters include the aortic blood pressure waveform, blood flow velocity waveform, and blood flow rate waveform.

[0060] refer to Figure 3 As shown, the coupling algorithm between the one-dimensional hemodynamic model and the zero-dimensional ternary Windkessel model can be implemented by equation (10), which is expressed as: (10) in Characteristic variables representing propagation forward along the central axis of the blood vessel. This indicates the propagation speed of the feature variable at the next time step. Z art The characteristic impedance of the distal aorta. Indicates the current time step. Indicates the next time step. This represents the outlet node of the blood vessel in a one-dimensional hemodynamic model. d coordinates t Indicates the time step of the calculation. K A parameter representing the stiffness of the aorta. This represents the outlet node of the blood vessel in a one-dimensional hemodynamic model. d The cross-sectional area of ​​the blood vessel at the next time step. A 0 represents pressure. P The cross-sectional area of ​​the blood vessel at 0°C Indicates the carotid-femoral pulse wave velocity. Blood density, A The cross-sectional area of ​​the blood vessel. U The average axial flow velocity is the cross-sectional velocity of the blood vessel. For the terminal outlet node of the blood vessel dThe average axial flow velocity across the blood vessel cross-section at the next time step For the next time step, the systemic arterial blood pressure, P 0 represents the reference pressure. The cross-sectional area of ​​the blood vessel at the last node d of the 1D blood vessel outlet can be obtained by solving the above system of equations. A and the average axial velocity of the blood vessel cross section U The cross-sectional area of ​​the blood vessel A Substituting into equation (1) yields the blood pressure at the last node d of the aorta in the one-dimensional hemodynamic model. Multiplying the vessel cross-sectional area A by the blood flow velocity U gives the blood flow rate at the last node d of the aorta. Based on arterial blood pressure waveform time-series data... P(t) Determine the blood pressure at the first node of the aorta in the one-dimensional hemodynamic model, and calculate the blood flow velocity and blood flow rate at the first node. Finally, based on the blood pressure, blood flow velocity, and blood flow rate at the first node of the aorta and the blood pressure, blood flow velocity, and blood flow rate at the last node d, obtain the blood pressure waveform, blood flow velocity waveform, and blood flow rate waveform of the aorta based on the governing equation (1) of the one-dimensional hemodynamic model.

[0061] In one embodiment of this application, the characteristic impedance of the distal aorta in the zero-dimensional ternary Windkessel model Z art It can be obtained using the following formula (6), and the expression of formula (6) is: (6) Blood density ρ Set to 1060 kg / m 3 ; Carotid-femoral pulse wave velocity (Carotid-femoral pulse wave velocity) Measurements must be taken while the subject is in a supine position. The diastolic diameter of the distal aorta can be obtained by measuring the diameter of the subject using echocardiography.

[0062] In one embodiment of this application, in order to further improve the accuracy of the output aortic hemodynamic waveform characteristic parameters of the preset aortic hemodynamic coupling model, this embodiment may also introduce a calibration mechanism at the initial cardiac cycle of measurement, that is, using the stroke volume measured non-invasively by echocardiography as a reference value to adaptively adjust the peripheral systemic arterial resistance in the preset aortic hemodynamic coupling model. This process continues until the stroke volume output by the preset aortic hemodynamic coupling model has an error of less than 1% or is completely consistent with the non-invasive measurement value from echocardiography. It should be noted that stroke volume measured by other types of non-invasive measurement methods (such as impedance analysis, pulse wave analysis, or photoplethysmography) can also be used as a reference value to adaptively adjust the peripheral systemic arterial resistance in the preset aortic hemodynamic coupling model. This application does not impose any fixed restrictions on it.

[0063] Step S102: Determine cardiac output based on the characteristic parameters of aortic hemodynamic waveform.

[0064] After obtaining the blood flow waveform of the aorta, the blood flow waveform within a single cardiac cycle can be integrated over time to obtain the stroke volume; finally, the stroke volume is combined with the heart rate to calculate the cardiac output.

[0065] When using a dynamic non-invasive pulse-wave blood pressure monitor to collect continuous arterial blood pressure waveform time-series data P(t) At the same time, the continuous arterial blood pressure waveform time series data will be processed. P(t) By inputting the data into a preset aortic hemodynamic coupling model and solving the model, the blood pressure waveform, blood flow velocity waveform, and blood flow waveform of the aorta can be calculated in real time and continuously. The flow waveform within a single cardiac cycle is integrated over time to obtain the stroke volume, and combined with heart rate calculations, the corresponding cardiac output can be continuously obtained. Thus, the method described in this application achieves real-time continuous measurement and output of cardiac output.

[0066] This application proposes a model-driven method for measuring arterial hemodynamics. It employs a one-dimensional hemodynamic model to simulate aortic blood flow, while a zero-dimensional multi-element elastic cavity model characterizes peripheral vascular resistance, compliance, and microcirculation perfusion characteristics, accurately reproducing peripheral blood flow impedance and buffering effects. This constructs a coupled one-dimensional and zero-dimensional aortic hemodynamic model. The one-dimensional model accurately depicts blood flow within the aorta and pulse wave propagation and reflection, achieving high-precision solutions for blood pressure, flow velocity, and flow rate waveforms. The zero-dimensional model simulates peripheral arterial blood flow and serves as the boundary condition for the one-dimensional model, making the overall blood flow simulation more closely resemble real physiological conditions. Simultaneously, non-invasive data is used for individualized calibration of model parameters, further improving the overall accuracy of hemodynamic measurements. Furthermore, this method utilizes non-invasive equipment for data acquisition and testing, avoiding the risk of catheter-related bloodstream infections that may arise from invasive procedures. This not only simplifies the testing process but also significantly improves the safety and patient tolerance of clinical applications, providing a reliable solution for safer and more convenient medical testing.

[0067] Further, refer to Figure 4As shown, in order to better implement the model-driven arterial hemodynamic measurement method in any of the above embodiments, based on the above model-driven arterial hemodynamic measurement method, this application embodiment also provides a model-driven arterial hemodynamic measurement device 1, which includes a waveform parameter acquisition module 11 and a cardiac output acquisition module 12.

[0068] The waveform parameter acquisition module 11 is used to collect arterial blood pressure waveform time-series data within a preset cardiac cycle, input the arterial blood pressure waveform time-series data into a preset aortic hemodynamic coupling model, and obtain aortic hemodynamic waveform characteristic parameters.

[0069] The cardiac output acquisition module 12 is used to determine the cardiac output based on the characteristic parameters of the aortic hemodynamic waveform.

[0070] The preset aortic hemodynamic coupling model is formed by coupling a one-dimensional hemodynamic model that simulates the aortic blood vessel transmission characteristics with a zero-dimensional multi-element elastic cavity model that simulates the peripheral arterial circulation impedance characteristics.

[0071] Furthermore, the waveform parameter acquisition module 11 is specifically used for: The formula for calculating the stiffness parameter of the aorta in the preset aortic hemodynamic coupling model is as follows: (4) in K A parameter representing the stiffness of the aorta. Indicates blood density, This indicates the carotid-femoral artery pulse wave velocity.

[0072] Furthermore, the waveform parameter acquisition module 11 is specifically used for: The initial value calculation formula for peripheral systemic arterial resistance in the pre-defined aortic hemodynamic coupling model is as follows: (8) in, Indicates peripheral systemic arterial resistance. Indicates the reference center output quantity. Indicates mean arterial pressure. This indicates capillary blood pressure. Indicates brachial artery diastolic pressure. This indicates the systolic blood pressure of the brachial artery.

[0073] Furthermore, the waveform parameter acquisition module 11 is specifically used for: The formula for calculating peripheral systemic artery compliance in the pre-defined aortic hemodynamic coupling model is as follows: (7) in, Indicates peripheral systemic arterial compliance. This indicates the reference to the total arterial compliance of a normal adult human body. This indicates the subject's weight. Indicates standard reference weight. Indicates the carotid-femoral pulse wave velocity. Indicates blood density, Indicates the length of the aorta. This represents the diameter of the aorta at the axial coordinate x.

[0074] Furthermore, the waveform parameter acquisition module 11 is specifically used for: The formula for calculating the length of the aorta in the pre-defined aortic hemodynamic coupling model is as follows: or (3) in, Indicates the length of the aorta. Indicates the height of male subjects. This indicates the height of the female subject. Furthermore, the waveform parameter acquisition module 11 is specifically used for: The peripheral systemic arterial resistance in the pre-defined aortic hemodynamic coupling model is adaptively corrected using stroke volume measured by a pre-defined non-invasive measurement method.

[0075] Furthermore, the waveform parameter acquisition module 11 is specifically used for: Arterial blood pressure waveform time-series data were collected using a non-invasive blood pressure monitor.

[0076] Furthermore, the waveform parameter acquisition module 11 is specifically used for: The arterial blood pressure waveform time series data is the aortic blood pressure waveform time series data.

[0077] This application also provides a device, such as... Figure 5 As shown, the device 2 includes: at least one processor 20, a memory 21, and a computer program 22 stored in the memory 21 and executable on at least one processor 20. When the processor 20 executes the computer program 22, it implements the steps in any of the above method embodiments, or when the processor 20 executes the computer program 22, it implements the functions of each module / unit in the above device embodiments.

[0078] For example, computer program 22 may be divided into one or more modules / units, one or more of which are stored in memory and executed by a processor to complete this application. The one or more modules / units may be a series of computer program instruction segments capable of performing a specific function, which describe the execution process of computer program 22 in the device.

[0079] Those skilled in the art will understand that Figure 5 This is merely an example of a device and does not constitute a limitation on the device. It may include more or fewer components than shown, or combinations of certain components, or different components. For example, the device may also include input / output devices, network access devices, buses, etc.

[0080] The aforementioned processor can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), or field-programmable gate arrays (FPGAs). Programmable Gate Array (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor can be a microprocessor or any conventional processor.

[0081] Memory can be an internal storage unit of a device, such as a hard drive or RAM. Memory can also be an external storage device, such as a plug-in hard drive, Smart Media Card (SMC), Secure Digital (SD) card, or Flash Card. Furthermore, memory can include both internal and external storage units.

[0082] This application embodiment also provides a readable storage medium storing a computer program 22, which, when executed by a processor, implements the steps in the above-described method embodiments.

[0083] This application provides a computer program product that, when run on a device, enables a mobile terminal to execute the steps described in the various method embodiments above.

[0084] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the methods of the above embodiments of this application can be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. A computer-readable medium can include at least: any entity or device capable of carrying computer program code to a photographing device / terminal device, a recording medium, a computer memory, a read-only memory (ROM), a random access memory (RAM), an electrical carrier signal, a telecommunication signal, and a software distribution medium. Examples include USB flash drives, portable hard drives, magnetic disks, or optical disks. In some jurisdictions, according to legislation and patent practice, computer-readable media cannot be electrical carrier signals or telecommunication signals.

[0085] In the above embodiments, the descriptions of each embodiment have different focuses. For parts that are not described in detail or recorded in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0086] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0087] In the embodiments provided in this application, it should be understood that the disclosed apparatus / device and method can be implemented in other ways. For example, the apparatus / device embodiments described above are merely illustrative. For instance, the division of modules or units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or units may be electrical, mechanical, or other forms.

[0088] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0089] The above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application, and should all be included within the protection scope of this application.

Claims

1. A model-driven method for measuring arterial hemodynamics, characterized in that, include: Collect time-series data of arterial blood pressure waveform within a preset cardiac cycle, and input the time-series data of arterial blood pressure waveform into a preset aortic hemodynamic coupling model to obtain aortic hemodynamic waveform characteristic parameters; Cardiac output is determined based on the aforementioned aortic hemodynamic waveform characteristic parameters; The preset aortic hemodynamic coupling model is formed by coupling a one-dimensional hemodynamic model that simulates the aortic blood vessel transmission characteristics with a zero-dimensional multi-element elastic cavity model that simulates the peripheral arterial circulation impedance characteristics.

2. The measurement method according to claim 1, characterized in that, The formula for calculating the stiffness parameter of the aorta in the preset aortic hemodynamic coupling model is as follows: in K A parameter representing the stiffness of the aorta. Indicates blood density, This indicates the carotid-femoral artery pulse wave velocity.

3. The measurement method according to claim 1, characterized in that, The initial value calculation formula for peripheral systemic arterial resistance in the preset aortic hemodynamic coupling model is as follows: in, Indicates peripheral systemic arterial resistance. Indicates the reference center output quantity. Indicates mean arterial pressure. This indicates capillary blood pressure. Indicates brachial artery diastolic pressure. This indicates the systolic blood pressure of the brachial artery.

4. The measurement method according to claim 1, characterized in that, The formula for calculating peripheral systemic artery compliance in the pre-defined aortic hemodynamic coupling model is as follows: in, Indicates peripheral systemic arterial compliance. This indicates the reference to the total arterial compliance of a normal adult human body. This indicates the subject's weight. Indicates standard reference weight. Indicates the carotid-femoral pulse wave velocity. Indicates blood density, Indicates the length of the aorta. This represents the diameter of the aorta at the axial coordinate x.

5. The measurement method according to claim 1, characterized in that, The formula for calculating the length of the aorta in the preset aortic hemodynamic coupling model is as follows: or in, Indicates the length of the aorta. Indicates the height of male subjects. This indicates the height of the female test subjects.

6. The measurement method according to any one of claims 1-5, characterized in that, The peripheral systemic arterial resistance in the preset aortic hemodynamic coupling model is adaptively corrected using the stroke volume measured by a preset non-invasive measurement method.

7. The measurement method according to any one of claims 1-5, characterized in that, The arterial blood pressure waveform time series data is the aortic blood pressure waveform time series data.

8. A model-driven arterial hemodynamic measurement device, characterized in that, Includes a waveform parameter acquisition module and a cardiac output quantity acquisition module; The waveform parameter acquisition module is used to collect arterial blood pressure waveform time-series data within a preset cardiac cycle, and input the arterial blood pressure waveform time-series data into a preset aortic hemodynamic coupling model to obtain aortic hemodynamic waveform characteristic parameters. The cardiac output acquisition module is used to determine the cardiac output based on the aortic hemodynamic waveform characteristic parameters. The preset aortic hemodynamic coupling model is formed by coupling a one-dimensional hemodynamic model that simulates the aortic blood vessel transmission characteristics with a zero-dimensional multi-element elastic cavity model that simulates the peripheral arterial circulation impedance characteristics.

9. A device, characterized in that, include: At least one processor, a memory, and a computer program stored in the memory and executable on at least one processor, wherein the processor, when executing the computer program, implements the method as claimed in any one of claims 1 to 7.

10. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by a processor, it implements the method as described in any one of claims 1 to 7.

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