Parameter identification method of lumped parameter model of body circulation

Abstract

This invention discloses a parameter identification method for a lumped parameter model of systemic circulation, belonging to the field of lumped parameter model technology. The method includes: constructing the state equation of the lumped parameter model of systemic circulation based on Kirchhoff's voltage and current laws to obtain the systemic circulation control equation; calculating the duration ratio of systolic to diastolic phases and stroke volume based on routine clinical measurement data, constructing classic aortic pressure and flow waveforms, and performing registration processing; calculating central venous pressure and flow based on routine clinical measurement data; and using the registered aortic inlet pressure and flow, central venous pressure and flow, and systemic circulation control equations to calculate the values ​​of each parameter in the parameter model. This invention, by periodically stretching the classic reference waveform, matches the waveform extreme values ​​with the patient's measured blood pressure and cardiac output, indirectly reconstructing the aortic inlet pressure and flow curve reflecting individual characteristics under non-invasive conditions, significantly improving the model's individualization and clinical compatibility.

Description

Technical Field

[0001] This invention relates to the field of lumped parameter model technology, and in particular to a parameter identification method for a lumped parameter model of a systemic circulation. Background Technology

[0002] Currently, lumped parameter models are widely used to simulate the human cardiovascular system, expressing the relationship between blood vessel resistance, capacitance, and flow through equivalent circuits. The systemic circulation module is a key component, involving the aorta, systemic arteries, microcirculation, and central veins.

[0003] In traditional systemic circulation modeling methods, the vascular resistance and compliance parameters required for systemic circulation models are typically obtained using the following methods: ① Based on anatomical or literature experience values; ② Invasive measurements (such as obtaining flow or pressure via catheter); ③ Multi-parameter fitting inversion (relies on large-scale simulation optimization).

[0004] The above method has the following drawbacks: ① Poor individual adaptability: Empirical values ​​cannot reflect individual differences among patients; ② Clinically infeasible: Flow rate and aortic pressure are difficult to measure accurately and non-invasively; ③ High uncertainty in inversion: High-dimensional parameter optimization is prone to getting trapped in local optima.

[0005] Therefore, those skilled in the art are dedicated to developing a parameter identification method for a lumped parameter model of the systemic circulation. Summary of the Invention

[0006] In view of the above-mentioned deficiencies of the prior art, the technical problem to be solved by the present invention is that traditional lumped parameter models mainly rely on empirical values ​​or invasive measurements to obtain aortic pressure and flow. The former lacks individual variability, and the latter is not feasible in routine clinical diagnosis due to its invasiveness, resulting in the inability to obtain patient-specific input boundary waveforms.

[0007] To achieve the above objectives, the present invention provides a parameter identification method for a systemic circulation lumped parameter model, the method comprising the following steps: S101: Based on Kirchhoff's voltage law and Kirchhoff's current law, construct the state equations of the lumped parameter model of the volume cycle, and obtain the control equations of the volume cycle based on the state equations; S103: Collect routine clinical measurement data, calculate the ratio of systolic to diastolic duration and stroke volume based on the routine clinical measurement data, and construct classic aortic pressure waveform and classic aortic flow waveform; S105: Perform registration processing on the classic aortic pressure waveform and the classic aortic flow waveform; S107: Calculate central venous pressure and central venous flow based on the aforementioned routine clinical measurement data; S109: Using the registered aortic inlet pressure, the registered aortic inlet flow rate, the central venous pressure, and the central venous flow rate, calculate the values ​​of each parameter in the systemic circulation lumped parameter model through the systemic circulation control equation.

[0008] Further, in step S101, the state equation is:

[0009] The systemic circulation control equation is:

[0010] in, The pressure at the aortic inlet. Central venous pressure, Aortic inlet flow, Central venous flow, To increase aortic resistance, To reduce proximal aortic resistance, For systemic venous resistance, For systemic arterial resistance, For upper limb resistance, Aortic compliance, For systemic arterial compliance, The blood flow rate is the equivalent resistance of the systemic circulation. The pressure at the equivalent intermediate node of the body circulation. This is the equivalent resistance.

[0011] Further, in step S103, the routine clinical measurement data includes systolic blood pressure, diastolic blood pressure and heart rate, wherein the systolic blood pressure and the diastolic blood pressure are collected using a brachial artery blood pressure monitor, and the heart rate is collected by echocardiography.

[0012] Further, in step S105, the registration process for the classic aortic pressure waveform includes the following sub-steps: S10511: Adjust the time axis: Stretch or contract the period of the classic pressure waveform to adapt the period to the patient's cardiac cycle, and adjust the time ratio of the systolic and diastolic segments in the waveform according to the patient's systolic and diastolic duration ratio. S10512: Diastolic pressure registration: Shift the classic pressure waveform curve vertically so that the minimum value of the curve is equal to the patient's diastolic pressure;

[0013] S10513: Calculate the scaling factor: Match the maximum value of the classical pressure waveform to the patient's systolic blood pressure and calculate the scaling factor:

[0014] S10514: Constructing patient-specific pressure curves:

[0015] S10515: The pressure curve was fitted using an 18th-order Fourier series to obtain the registered aortic inlet pressure:

[0016] in, The pressure waveform curve after translation For classic aortic pressure, For diastolic blood pressure, For systolic pressure, This is the scaling factor. Heart rate, For time, Let be the order of the Fourier series. These are the coefficients obtained from the fitting.

[0017] Further, in step S105, the registration process for the classic aortic flow waveform includes the following sub-steps: S10521: Adjust the time axis: Stretch or contract the period of the classic flow waveform to adapt the period to the patient's cardiac cycle, and adjust the time ratio of the systolic and diastolic segments in the classic flow waveform according to the patient's systolic and diastolic duration ratio. S10522: Calculate the scaling factor: Scalculate the area enclosed by the classic aortic flow waveform curve and the coordinate axes to register the patient's stroke volume:

[0018] S10523: Constructing patient-specific flow curves:

[0019] S10524: The classical aortic flow curve was fitted using an 18th-order Fourier series to obtain the registered aortic inlet flow rate:

[0020] in, For classic aortic flow, For stroke volume, This is the scaling factor. These are the coefficients obtained from the fitting.

[0021] Furthermore, in step S107, the central venous pressure is calculated using the following method:

[0022] in, This represents the mean central venous pressure. This represents the amplitude of fluctuations in central venous pressure.

[0023] Furthermore, in step S107, the central venous flow rate is calculated using the following method:

[0024] in, This represents the average central venous flow. The amplitude of central venous flow fluctuation. This refers to the phase angle parameter.

[0025] Further, in step S109, when calculating each parameter in the systemic circulation lumped parameter model, the following steps are included: Integrating the systemic circulation control equation over the cardiac cycle enables the calculation of the steady resistance parameters in the systemic circulation lumped parameter model. The impedance parameters in the lumped parameter model of the body circulation are calculated by performing a Fourier transform on the body circulation control equations.

[0026] Furthermore, the steady drag parameters in the lumped parameter model of the volumetric circulation are calculated using the following method:

[0027] in, This is the mean pressure at the aortic inlet. This represents the mean central venous pressure. The mean flow rate at the aortic inlet. This represents the average central venous flow.

[0028] Furthermore, the impedance parameters in the lumped parameter model of the volume cycle are calculated using the following method:

[0029] in, The aortic pressure after Fourier transform. Central venous pressure after Fourier transform. The aortic flow rate after Fourier transform. Central venous flow after Fourier transform. Aortic input impedance, For central venous output impedance, The imaginary unit, Let be the angular frequency of the nth harmonic.

[0030] In a preferred embodiment of the present invention, compared with the prior art, the present invention has the following beneficial technical effects: 1. This invention adapts the classic reference waveform to the cardiac cycle by periodically stretching it, and matches the waveform extreme values ​​with the patient's measured blood pressure and cardiac output using translation and scaling factors. This allows for the indirect reconstruction of the aortic inlet pressure and flow curve, which reflects the individual characteristics of the patient, under non-invasive conditions. This achieves completely non-invasive parameter identification, and the constructed input waveform can be adapted to the heart rate, blood pressure, and ventricular pumping capacity of different patients, significantly improving the individualization and clinical compatibility of the model.

[0031] 2. This invention utilizes the linear first-order differential equation characteristics of a lumped-parameter model, simplifying the time-domain convolution structure into a frequency-domain algebraic product by fitting the registered waveform using Fourier series. Combining the formulas for calculating steady-state resistance (integral method) and systemic impedance, the desired parameters are directly analyzed, avoiding complex optimization processes. This method offers fast calculation speed, strong stability, and unique and repeatable results, facilitating integration into real-time clinical auxiliary diagnostic software.

[0032] The following will further explain the concept, specific structure, and technical effects of the present invention in conjunction with the accompanying drawings, so as to fully understand the purpose, features, and effects of the present invention. Attached Figure Description

[0033] Figure 1 This is a schematic diagram of the parameter identification method steps of a body cycle lumped parameter model according to a preferred embodiment of the present invention; Figure 2This is a schematic diagram of the basic lumped parameter model of a preferred embodiment of the present invention; Figure 3 This is a schematic diagram of a classic pressure waveform of a preferred embodiment of the present invention; Figure 4 This is a schematic diagram of a classic flow waveform of a preferred embodiment of the present invention; Figure 5 This is a schematic diagram of pressure waveform registration according to a preferred embodiment of the present invention; Figure 6 This is a schematic diagram of flow waveform registration according to a preferred embodiment of the present invention. Detailed Implementation

[0034] The following description, with reference to the accompanying drawings, illustrates several preferred embodiments of the present invention to make its technical content clearer and easier to understand. The present invention can be embodied in many different forms, and the scope of protection of the present invention is not limited to the embodiments mentioned herein.

[0035] In the accompanying drawings, components with the same structure are indicated by the same numerical designation, and components with similar structures or functions are indicated by similar numerical designations. The dimensions and thicknesses of each component shown in the drawings are arbitrary, and the present invention does not limit the dimensions and thicknesses of each component. To make the illustrations clearer, the thickness of some components has been appropriately exaggerated in the drawings.

[0036] like Figure 1 As shown, existing systemic circulation lumped parameter models primarily rely on empirical values ​​or invasive measurements to obtain aortic pressure and flow, leading to the inability to acquire patient-specific input boundary waveforms. This invention provides a parameter identification method for systemic circulation lumped parameter models, used to estimate systemic circulation parameter values ​​in the lumped parameter model of the human cardiovascular system. Specifically, it is used to accurately identify key parameters such as systemic arterial compliance and peripheral resistance based on the lumped parameter model, and can be applied to scenarios such as individualized surgical planning, clinical auxiliary diagnosis, circulatory system simulation, and disease mechanism research. The parameter identification method for systemic circulation lumped parameter models provided in this invention specifically includes the following steps: S101: Based on Kirchhoff's voltage law and Kirchhoff's current law, construct the state equations of the lumped parameter model of the volume cycle, and obtain the control equations of the volume cycle based on the state equations. In this embodiment, the state equation of the volume cyclic lumped parameter model constructed based on Kirchhoff's voltage law and current law is as follows:

[0037] The constructed systemic circulation control equations are as follows:

[0038] in, The pressure at the aortic inlet. Central venous pressure, Aortic inlet flow, Central venous flow, To increase aortic resistance, To reduce proximal aortic resistance, For systemic venous resistance, For systemic arterial resistance, For upper limb resistance, Aortic compliance, For systemic arterial compliance, The blood flow rate is the equivalent resistance of the systemic circulation. The pressure at the equivalent intermediate node of the body circulation. This is the equivalent resistance.

[0039] S103: Collect routine clinical measurement data, calculate the ratio of systolic to diastolic duration and stroke volume based on the routine clinical measurement data, and construct classic aortic pressure waveform and classic aortic flow waveform.

[0040] In this embodiment, the collected routine clinical measurement data include systolic blood pressure, diastolic blood pressure, and heart rate. Systolic blood pressure and diastolic blood pressure are collected using a brachial artery blood pressure monitor, and heart rate is collected using echocardiography.

[0041] S105: Perform registration processing on the classic aortic pressure waveform and the classic aortic flow waveform.

[0042] The registration process for the classic aortic pressure waveform includes the following sub-steps: S10511: Adjust the time axis: Stretch or contract the period of the classic pressure waveform to match the patient's cardiac cycle, and adjust the time ratio of the systolic and diastolic segments in the waveform according to the patient's systolic and diastolic duration ratio. S10512: Diastolic pressure registration: The classic pressure waveform curve is shifted up and down to make the minimum value of the curve equal to the patient's diastolic pressure;

[0043] S10513: Calculate the scaling factor: Match the maximum value of the classic pressure waveform to the patient's systolic blood pressure and calculate the scaling factor:

[0044] S10514: Constructing patient-specific pressure curves:

[0045] S10515: The pressure curve was fitted using an 18th-order Fourier series to obtain the registered aortic inlet pressure.

[0046] in, The pressure waveform curve after translation For classic aortic pressure, For diastolic blood pressure, For systolic pressure, This is the scaling factor. Heart rate, For time, Let be the order of the Fourier series. These are the coefficients obtained from the fitting.

[0047] The registration process for the classic aortic flow waveform includes the following sub-steps: S10521: Adjust the time axis: Stretch or contract the period of the classic flow waveform to match the patient's cardiac cycle, and adjust the time ratio of the systolic and diastolic segments in the classic flow waveform according to the patient's systolic and diastolic duration ratio. S10522: Calculate the scaling factor: Scaling the area enclosed by the classic aortic flow waveform curve and the coordinate axes to register the patient's stroke volume:

[0048] S10523: Constructing patient-specific flow curves:

[0049] S10524: The classic aortic flow curve was fitted using an 18th-order Fourier series to obtain the aortic inlet flow rate after registration.

[0050] in, For classic aortic flow, For stroke volume, This is the scaling factor. These are the coefficients obtained from the fitting.

[0051] S107: Calculate central venous pressure and central venous flow based on routine clinical measurement data; In this embodiment, the central venous pressure is calculated using the following method:

[0052] in, This represents the mean central venous pressure. This represents the amplitude of fluctuations in central venous pressure.

[0053] The following calculation method is used when calculating central venous flow:

[0054] in, This represents the average central venous flow. The amplitude of central venous flow fluctuation. This refers to the phase angle parameter.

[0055] S109: Using the registered aortic inlet pressure, registered aortic inlet flow, central venous pressure, and central venous flow, calculate the values ​​of each parameter in the lumped parameter model of the systemic circulation through the systemic circulation control equation.

[0056] In this embodiment, when calculating the parameters in the lumped parameter model of the volumetric circulation, the main parameters include the steady drag parameter and the impedance parameter in the lumped parameter model of the volumetric circulation.

[0057] 1) Calculation of steady drag parameters in the lumped parameter model of the body circulation

[0058] By integrating the systemic circulatory control equations over the cardiac cycle, the steady resistance parameters in the systemic circulatory lumped parameter model can be calculated.

[0059] The following method is used to calculate the steady drag parameters in the lumped parameter model of the body circulation:

[0060] in, This is the mean pressure at the aortic inlet. This represents the mean central venous pressure. The mean flow rate at the aortic inlet. This represents the average central venous flow.

[0061] 2) Calculation of impedance parameters in the lumped parameter model of the body circulation

[0062] By performing a Fourier transform on the systemic circulation control equations, the impedance parameters in the systemic circulation lumped parameter model can be calculated.

[0063] The impedance parameters in the lumped parameter model of the volume cycle are calculated using the following method:

[0064] in, The aortic pressure after Fourier transform. Central venous pressure after Fourier transform. The aortic flow rate after Fourier transform. Central venous flow after Fourier transform. Aortic input impedance, For central venous output impedance, The imaginary unit, Let be the angular frequency of the nth harmonic.

[0065] Compared with existing technologies, the parameter identification method for the lumped-parameter model of the systemic circulation provided by this invention has the following beneficial technical effects: 1. Traditional lumped-parameter models primarily rely on empirical values ​​or invasive measurements to obtain aortic pressure and flow. The former lacks individual variability, while the latter is impractical in routine clinical diagnosis due to its invasiveness, resulting in the inability to obtain patient-specific input boundary waveforms. This invention proposes an individualized construction method for classic aortic pressure / flow waveforms based on non-invasive clinical data (systolic blood pressure, diastolic blood pressure, heart rate, stroke volume) through "time axis registration + amplitude scaling." By periodically stretching the classic reference waveform to match the cardiac cycle, and using translation and scaling factors to match the waveform extremes with the patient's measured blood pressure and cardiac output, the aortic inlet pressure and flow curve reflecting the individual characteristics of the patient can be indirectly reconstructed under non-invasive conditions. This achieves completely non-invasive parameter identification, and the constructed input waveform can be adapted to the heart rate, blood pressure, and ventricular pumping capacity of different patients, significantly improving the model's individualization and clinical compatibility.

[0066] 2. Traditional lumped parameter models rely heavily on "multi-parameter fitting and inversion" for parameter acquisition. This high-dimensional optimization algorithm is computationally intensive, converges slowly, and is prone to getting trapped in local optima, leading to high uncertainty and non-reproducibility of the identification results. This invention employs a frequency domain identification method based on Fourier transform, converting differential equations into algebraic equations for direct solution without the need for an iterative optimizer. Utilizing the linear first-order differential equation characteristics of the lumped parameter model, the time-domain convolution structure is simplified to an algebraic product in the frequency domain by fitting the registered waveform using Fourier series. Combined with the formulas for calculating steady-state resistance (integral method) and systemic impedance, the parameters to be determined are directly analyzed, avoiding complex optimization processes. This method offers fast computation speed, strong stability, and unique and reproducible results, facilitating integration into real-time clinical auxiliary diagnostic software.

[0067] 3. In clinical practice, it is extremely difficult to accurately measure changes in pressure and flow in the central venous system using non-invasive methods. Furthermore, the absence of the central venous system as the exit boundary of the systemic circulation prevents model closure, thus hindering accurate calculation of resistance and compliance at various levels of the systemic circulation. This invention proposes an approximation method based on the amplitude fluctuations related to the mean and heart rate, simplifying the boundary conditions at the central venous exit point. Considering the extremely small fluctuations in the central venous system, an approximate curve is constructed based on the mean, combined with a small amplitude fluctuation function induced by heart rate. This simplification, while ensuring the validity of physical laws, reduces extreme dependence on clinical data, resolving the contradiction between model closure and practical usability. This allows for parameter identification of the entire systemic circulation (from the aorta to the central venous system) even with only conventional ultrasound indicators.

[0068] The present invention will now be described in detail with reference to preferred embodiments.

[0069] This invention provides a parameter identification method for a lumped parameter model of the systemic circulation, which is used to estimate the values ​​of systemic circulation parameters in the lumped parameter model of the human cardiovascular system. In particular, it is used to accurately identify key parameters such as systemic arterial compliance and peripheral resistance based on the lumped parameter model, and can be applied to scenarios such as individualized surgical planning, clinical auxiliary diagnosis, circulatory system simulation and disease mechanism research.

[0070] The parameter identification method includes the following steps: Step 1: Define the inlet end as the aorta and the outlet end as the equivalent posterior central venous vein, and construct a basic lumped parameter model, such as... Figure 2 As shown.

[0071] Step 2: Based on Kirchhoff's voltage law and current law, establish the state equations for the lumped parameter model, as shown in the following formulas: (1) (2) (3) (4) Among them, P c1 P c2 Q represents the aortic inlet pressure and central venous pressure, respectively. c1 Q c2 R represents the aortic inlet flow and central venous flow, respectively. sv C represents systemic venous resistance. ao Indicates aortic compliance, C s R0 represents systemic arterial compliance and equivalent resistance.

[0072] The formula for the meaning of equivalent resistance R0 is: (5) Among them, R ao R represents the resistance of the ascending aorta. ub R represents upper limb resistance. pda Indicates decreased proximal aortic resistance, R s This indicates systemic arterial resistance.

[0073] Based on the formula for the equivalent resistance R0, the following volumetric control equations are obtained to describe the pressure-flow relationship at the inlet and outlet of the simplified lumped parameter model: (6) Because it is impossible to directly obtain complete pressure and flow curves at the aortic inlet using non-invasive methods in clinical practice, and it is also impossible to measure changes in pressure and flow in the central vein, it is impossible to accurately calculate the values ​​of various parameters of the systemic circulation system using analytical formulas for steady resistance and impedance. This ultimately prevents the calculation of lumped parameter models that address individual patient differences, and thus makes it impossible to calculate the values ​​of various parameters of the systemic circulation system. To solve these problems, we indirectly construct individualized input waveforms for each patient using routine clinical measurement data (such as echocardiography and cuff blood pressure measurement results). Considering that the essence of the lumped parameter model is a system of linear first-order differential equations, the Fourier transform simplifies the convolution structure to an algebraic product. Utilizing the explicit relationship between Fourier coefficients and the system frequency response, the unknown parameters can be directly solved, thus ultimately obtaining the values ​​of various parameters of the systemic circulation system, as detailed below: Step 3: Measure the patient's systolic blood pressure (P) using a brachial artery blood pressure monitor. sys and diastolic pressure P dia The patient's heart rate (HR) was measured using echocardiography. The ratio of systolic to diastolic duration was calculated based on the echocardiogram to obtain the classic aortic pressure waveform (P). ref (t), such as Figure 3 As shown.

[0074] For the classic aortic pressure waveform P ref (t) Registration is performed as follows: 1) Adjust the timeline For the classic pressure waveform P ref The periodic stretching or contraction of (t) is adjusted to match the patient's cardiac cycle; the time ratio of the systolic and diastolic segments in the waveform is adjusted according to the patient's systolic and diastolic duration ratio.

[0075] 2) Diastolic blood pressure registration

[0076] The curve is shifted vertically until its minimum value equals the measured diastolic blood pressure of the patient. The shift amount is calculated using the following formula: (9) in, The pressure waveform curve after translation.

[0077] 3) Calculate the scaling ratio

[0078] The maximum value of the pressure waveform is compared with the patient's systolic blood pressure P. sys Match and calculate the scaling factor k. p : (10) 4) Construct patient-specific stress curves: (11) 5) The aortic inlet pressure after registration was obtained by fitting the curve with an 18th-order Fourier series. The fitting method is as follows: (12) in, (HR is the heart rate measured by echocardiography); a0, A n and B n These are the coefficients obtained from the fitting.

[0079] Step 4: Calculate the patient's stroke volume (SV) based on echocardiography, and combine it with heart rate (HR) and the ratio of systolic to diastolic duration to obtain the classic aortic flow waveform (Q). ref (t), such as Figure 4 As shown.

[0080] For the classic aortic flow waveform Q ref (t) Registration is performed as follows: 1) Adjust the time axis: Adjust the classic flow waveform Q ref The periodic stretching or contraction of (t) is adjusted to match the patient's cardiac cycle; the time ratio of the systolic and diastolic segments in the waveform is adjusted according to the patient's systolic and diastolic duration ratio.

[0081] 2) Calculate the scaling factor: Scaling the area enclosed by the classical curve and the coordinate axis to register the patient's stroke volume SV (estimated from echocardiography).

[0082] The calculation formula is as follows: (13) 3) Construct patient-specific flow curves: (14) 4) The aortic inlet flow rate after registration was obtained by fitting the curve with an 18th-order Fourier series. The fitting method is as follows: (15) in, (HR is the heart rate measured by echocardiography); b0, C n and D n These are the coefficients obtained from the fitting.

[0083] Compared to the aorta, the pressure and flow fluctuations at the central vein are extremely small, and it is difficult to obtain its precise change curves non-invasively in clinical practice. Therefore, an approximation method is used to simplify the boundary conditions at the central vein outlet in order to achieve the model's closure and practical usability, as detailed in step 5.

[0084] Step 5: Estimate central venous pressure and flow

[0085] The central venous pressure P is estimated using the following formula. c2 (t): (16) in, This represents the mean central venous pressure, taken as 4 mmHg. (A) P This represents the amplitude of central venous pressure fluctuations, expressed as 1 mmHg. (HR is the heart rate measured by echocardiography).

[0086] Central venous flow Q can be estimated using the following formula. c2 (t): (17) in, The mean value of central venous flow is SV / T; AP represents the amplitude of central venous flow fluctuation, taken as 0.1. ; (HR is the heart rate measured by echocardiography). This refers to the phase angle parameter.

[0087] Step 6: Integrating the systemic circulation control equation over the cardiac cycle T yields the formula for calculating the steady-state resistance of the systemic circulation, which can then be used for steady-state analysis. (7) By performing a Fourier transform on the systemic circulation control equations, we can obtain the formula for calculating the systemic circulation impedance, which can then be used for impedance analysis. (8) Step 7: Substitute the registered aortic inlet pressure, registered aortic inlet flow, central venous pressure, and central venous flow into the formulas for calculating systemic circulation steady resistance and systemic circulation impedance.

[0088] Because in the equivalent resistance R0 of the body circulation module, R ao R ubR pda R sv and R s The values ​​differ by more than two orders of magnitude, therefore R is kept constant. ao R ub R pda R sv The value remains unchanged, thus determining R. s The values ​​are then determined, ultimately yielding the values ​​of each parameter in the circulatory system.

[0089] The final calculation result is: R ao =0.05 mmHg·s·mL -1 R ub =0.28 mmHg·s·mL -1 R pda =0.05 mmHg·s·mL -1 R sv =0.05 mmHg·s·mL -1 .

[0090] This embodiment uses a simulated patient as the subject, and the main physiological parameters are set as follows: Systolic blood pressure (assuming measurement by a sphygmomanometer): 120 mmHg; Diastolic blood pressure (assuming measurement by a sphygmomanometer): 80 mmHg; Heart rate (assuming measurement by echocardiography): 75 bpm; Stroke volume (assuming estimation by echocardiography): 70 mL; Systolic to diastolic duration ratio (based on echocardiographic measurement): 0.4.

[0091] The implementation steps are as follows: [Classic Waveform Construction] Selecting the classic aortic pressure and flow waveform, we obtain the standard reference curve P. ref (t) (e.g.) Figure 3 (as shown) and Q ref (t) (e.g.) Figure 4 (As shown).

[0092] [Pressure Waveform Registration] Register according to the pressure waveform registration method (applicable to aortic inlet pressure). The registration result is as follows: Figure 5 As shown.

[0093] The registered pressure waveform was fitted using an 18th-order Fourier series, and the coefficients of its expression are as follows (rounded to three decimal places): a0 = 100.481; A n=[-12.809, -5.563, 1.706, 0.584, 1.351, 0.076, 0.059, -0.058, -0.310, -0.012, -0.238, 0.145, -0.051, 0.085, 0.037, 0.091, 0.016, -0.072]; B n =[6.404, -4.479, -3.327, -0.367, -0.191, 0.562, 0.165, 0.385, -0.205, -0.059, -0.277, -0.130, -0.010, -0.061, 0.002, 0.098, 0.196, 0.044]; [Flow Waveform Registration] Register according to the flow waveform registration method (applicable to aortic inlet flow). Registration result as follows: Figure 6 As shown.

[0094] The registered flow waveform was fitted using an 18th-order Fourier series, and the coefficients of the expression are as follows (rounded to three decimal places): b0 = 87.500; C n =[52.622, -40.456, -60.762, -16.144, -20.158, -7.580, -0.174, -0.700, 1.788, 6.738, 2.151, 2.896, 4.770, 1.312, 0.499, 1.067, 0.083, 0.408]; D n =[108.423, 80.624, 8.024, -12.449, -4.336, -17.488, -8.533, -6.626, -8.903, -3.767, 0.811, -2.807, 1.130, 2.231, 0.282, 1.215, 0.899, 0.276]; [Central Venous Pressure and Flow Calculation] The pressure waveform and flow waveform of the central vein are calculated based on the central vein flow and pressure estimation method.

[0095]

Parameter Calculation of the Model

[0096] Compared with existing technologies, the embodiments of the present invention do not depend on a specific form of lumped parameter model structure, but are applicable to all volumetric circulation module models consisting only of a resistance term (R) and a compliance term (C). That is: a. For any volume loop module model consisting only of resistors (R) and capacitors (C) (regardless of whether the circuit is in series, parallel or composite structure), as long as the basic state equation can be analytically described, the method of this invention can be used for parameter identification; b. The resistance terms in the model can be in a combined form (equivalent resistance) or a split form (e.g., dividing aortic resistance into ascending aortic resistance Rao and descending aortic proximal resistance Rpda), and this method can adapt to both. Because this invention is based on frequency domain identification of system response, it has strong compatibility in modeling resistance terms.

[0097] Therefore, this invention is applicable not only to classic Windkessel models (such as binary / ternary models), but also to rewritten or combined volume cyclic lumped parameter model structures.

[0098] Compared with the prior art, the embodiments of the present invention have the following advantages: ① Non-invasive and efficient: The entire process does not rely on the original aortic measurement and only requires conventional ultrasound; ② Individualized modeling: Applicable to patients with different heart rates, SV, and blood pressure; ③ No optimizer required: Avoids getting trapped in local optima, and the result is unique and repeatable; ④ Frequency domain method is efficient and stable: Fourier transform simplifies calculations and improves robustness; ⑤ Strong clinical compatibility: It is easy to integrate into ultrasound assessment software and preoperative planning systems.

[0099] The preferred embodiments of the present invention have been described in detail above. It should be understood that those skilled in the art can make numerous modifications and variations based on the concept of the present invention without creative effort. Therefore, all technical solutions that can be obtained by those skilled in the art based on the concept of the present invention through logical analysis, reasoning, or limited experimentation on the basis of existing technology should be within the scope of protection defined by the claims.

Claims

1. A method for parameter identification in a cyclic lumped parameter model, characterized in that, The method includes the following steps: S101: Based on Kirchhoff's voltage law and Kirchhoff's current law, construct the state equations of the lumped parameter model of the volume cycle, and obtain the control equations of the volume cycle based on the state equations; S103: Collect routine clinical measurement data, calculate the ratio of systolic to diastolic duration and stroke volume based on the routine clinical measurement data, and construct classic aortic pressure waveform and classic aortic flow waveform; S105: Perform registration processing on the classic aortic pressure waveform and the classic aortic flow waveform; S107: Calculate central venous pressure and central venous flow based on the aforementioned routine clinical measurement data; S109: Using the registered aortic inlet pressure, the registered aortic inlet flow rate, the central venous pressure, and the central venous flow rate, calculate the values ​​of each parameter in the systemic circulation lumped parameter model through the systemic circulation control equation.

2. The method as described in claim 1, characterized in that, In step S101, the state equation is: The systemic circulation control equation is: in, The pressure at the aortic inlet. Central venous pressure, Aortic inlet flow, Central venous flow, To increase aortic resistance, To reduce proximal aortic resistance, For systemic venous resistance, For systemic arterial resistance, For upper limb resistance, Aortic compliance, For systemic arterial compliance, The blood flow rate is the equivalent resistance of the systemic circulation. The pressure at the equivalent intermediate node of the body circulation. This is the equivalent resistance.

3. The method as described in claim 2, characterized in that, In step S103, the routine clinical measurement data includes systolic blood pressure, diastolic blood pressure, and heart rate. The systolic blood pressure and the diastolic blood pressure are collected using a brachial artery blood pressure monitor, and the heart rate is collected using echocardiography.

4. The method as described in claim 3, characterized in that, In step S105, the registration process for the classic aortic pressure waveform includes the following sub-steps: S10511: Adjust the time axis: Stretch or contract the period of the classic pressure waveform to adapt the period to the patient's cardiac cycle, and adjust the time ratio of the systolic and diastolic segments in the waveform according to the patient's systolic and diastolic duration ratio. S10512: Diastolic pressure registration: Shift the classic pressure waveform curve vertically so that the minimum value of the curve is equal to the patient's diastolic pressure; S10513: Calculate the scaling factor: Match the maximum value of the classical pressure waveform to the patient's systolic blood pressure and calculate the scaling factor: S10514: Constructing patient-specific pressure curves: S10515: The pressure curve was fitted using an 18th-order Fourier series to obtain the registered aortic inlet pressure: in, The pressure waveform curve after translation For classic aortic pressure, For diastolic blood pressure, For systolic pressure, This is the scaling factor. Heart rate, For time, Let be the order of the Fourier series. These are the coefficients obtained from the fitting.

5. The method as described in claim 4, characterized in that, In step S105, the registration process for the classic aortic flow waveform includes the following sub-steps: S10521: Adjust the time axis: Stretch or contract the period of the classic flow waveform to adapt the period to the patient's cardiac cycle, and adjust the time ratio of the systolic and diastolic segments in the classic flow waveform according to the patient's systolic and diastolic duration ratio. S10522: Calculate the scaling factor: Scalculate the area enclosed by the classic aortic flow waveform curve and the coordinate axes to register the patient's stroke volume: S10523: Constructing patient-specific flow curves: S10524: The classical aortic flow curve was fitted using an 18th-order Fourier series to obtain the registered aortic inlet flow rate: in, For classic aortic flow, For stroke volume, This is the scaling factor. These are the coefficients obtained from the fitting.

6. The method as described in claim 5, characterized in that, In step S107, the central venous pressure is calculated using the following method: in, This represents the mean central venous pressure. This represents the amplitude of fluctuations in central venous pressure.

7. The method as described in claim 6, characterized in that, In step S107, the central venous flow rate is calculated using the following method: in, This represents the average central venous flow. The amplitude of central venous flow fluctuation. This refers to the phase angle parameter.

8. The method as described in claim 7, characterized in that, In step S109, calculating each parameter in the systemic circulation lumped parameter model includes: Integrating the systemic circulation control equation over the cardiac cycle enables the calculation of the steady resistance parameters in the systemic circulation lumped parameter model. The impedance parameters in the lumped parameter model of the body circulation are calculated by performing a Fourier transform on the body circulation control equations.

9. The method as described in claim 8, characterized in that, The steady drag parameters in the lumped parameter model of the volumetric circulation are calculated using the following method: in, This is the mean pressure at the aortic inlet. This represents the mean central venous pressure. The mean flow rate at the aortic inlet. This represents the average central venous flow.

10. The method as described in claim 9, characterized in that, The impedance parameters in the lumped parameter model of the volume cycle are calculated using the following method: in, The aortic pressure after Fourier transform. Central venous pressure after Fourier transform. The aortic flow rate after Fourier transform. Central venous flow after Fourier transform. Aortic input impedance, For central venous output impedance, The imaginary unit, Let be the angular frequency of the nth harmonic.

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