Method for measuring dynamic viscosity, storage modulus and equivalent load mass of blood sample

Abstract

The invention discloses a method for measuring the dynamic viscosity, the storage modulus and the equivalent load mass of a blood sample, and belongs to the field of blood coagulation analys.The method comprises the steps that a mechanical vibration system equivalent model is established when a blood viscoelastic sensor works, and the compliance relation of model parameters to the dynamic viscosity, the storage modulus and the equivalent load mass of the sample is obtained; the method comprises the following steps: establishing an equivalent circuit of a coil in a sensor, deducing an expression of a motional impedance modulus of the coil according to the equivalent circuit, and identifying model parameters through a model parameter identification method by utilizing frequency spectrum data of the motional impedance modulus; a plurality of gradients of standard viscosity liquid samples are adopted for experiments to obtain calibration coefficients, the dynamic viscosity, the storage modulus and the equivalent load mass are calculated according to the identified model parameters and the calibration coefficients, and through the steps, the dynamic viscoelasticity and the equivalent load mass of the sample in the blood coagulation process can be measured at the same time.

Description

Technical Field

[0001] This invention relates to the field of coagulation analysis, and in particular to methods for measuring the dynamic viscosity, storage modulus and equivalent loading mass of blood samples. Background Technology

[0002] During blood clotting, fibrin, platelets, and blood cells form a three-dimensional cross-linked network structure. Under the action of plasmin, fibrin dissolves. During this process, blood viscoelasticity changes. By detecting these changes in blood viscoelasticity using testing equipment, the coagulation process can be qualitatively or quantitatively analyzed. This helps doctors understand a patient's coagulation function, enabling accurate diagnosis and treatment.

[0003] CN201921454553.9 discloses a thromboelasticity detection sensor, the structure of which is referenced Figure 1 The sensor mainly comprises: a magnetic cap 1, a permanent magnet 2, a coil 3, a probe holder 4, a vibrating spring 5, a base plate 6, and a probe head 7. The permanent magnet 2 is fixed within the receiving hole at the top of the magnetic cap 1, forming a stable magnetic field within the air gap between the permanent magnet 2 and the magnetic cap 1. The top of the probe holder 4 is movably mounted on the bottom of the permanent magnet 2. The coil 3 is wound unidirectionally within the annular groove at the top of the probe holder 4, and is situated within the stable magnetic field. The connector of the coil 3 is led out. During operation, an alternating current flows through the coil 3, which experiences an alternating force in the stable magnetic field, causing it to vibrate along its central axis of symmetry. This vibration drives the probe holder 4 to move synchronously. The vibrating spring 5, fixed to the probe holder 4, provides the restoring force for the vibration. The probe head 7 is fixed to the probe holder 4, and its lower end is inserted into the blood being tested. The mechanical properties of the blood being tested affect the motion state of the sensor's moving parts.

[0004] Before blood coagulation, viscosity is dominant; as coagulation progresses, elasticity gradually plays a more significant role. Both viscosity and elasticity are important physical parameters reflecting coagulation function. Most existing detection technologies can only measure either viscosity or elasticity as a single parameter. Representative blood viscoelasticity testing equipment includes the thromboelastography (TEG) instrument from Haemonetics (USA), the rotational thromboelastometer (ROTEM) from Tem (Germany), and the platelet function analyzer (Sonoclot) from Sienco (USA). Instruments such as the TEG 5000, ROTEM delta, and TEG 6s essentially measure the shear elastic modulus of whole blood samples, reflecting the elastic properties of blood; while the Sonoclot coagulation and platelet function analyzer essentially measures the viscosity of whole blood samples. None of these instruments simultaneously measure viscosity and elasticity. The information reflected by the elasticity and viscosity parameters of blood in the coagulation system is not entirely the same; therefore, it is necessary to understand both elasticity and viscosity information during the coagulation process. Summary of the Invention

[0005] In order to overcome the shortcomings of the prior art, one of the objectives of this invention is to provide a blood sample measurement method that can simultaneously measure the dynamic viscosity (reflecting viscosity properties), storage modulus (reflecting elastic properties), and equivalent load mass during the coagulation process.

[0006] One of the objectives of this invention is achieved through the following technical solution: A method for measuring the dynamic viscosity, storage modulus, and equivalent loading mass of a blood sample, comprising the following steps: S1: Establish an equivalent model of the mechanical vibration system of the blood viscoelastic sensor during operation. In the equivalent model... In the formula, The spring constant of the equivalent spring. This is the total equivalent elastic coefficient of the sensor reed; The storage modulus of the sample; It is a constant determined by the geometry of the measuring cup and the probe; The damping coefficient of the equivalent damper; This represents the total damping coefficient of the sensor reeds; Indicates the radiation resistance when the reed radiates a sound field; The dynamic viscosity of the sample; The mass of the equivalent mass block; This represents the additional radiative mass when the sensor reed radiates the sound field. This represents the sum of the probe's own mass and the equivalent mass of the reed. This represents the equivalent load mass of the sample being tested. and relative constant Normalize, Let be the electromechanical coupling coefficient of the blood viscoelastic sensor, and let From the above formula, we can obtain: , In the formula, the coefficients and The expressions are respectively ; S2: Establish the equivalent circuit of the coil in the sensor. Based on the equivalent circuit, determine the motional impedance of the coil. , Angular frequency, The imaginary unit; The model is Normalized and Substitution get ,according to To establish a least-squares optimization model based on the spectrum, initial values ​​for the model parameter vector and determination of various experimental conditions are needed. The corresponding weights are used to perform nonlinear least squares fitting based on the parameter vector and the weights to obtain the parameters. and ; S3: Experiments were conducted using standard viscosity liquid samples with multiple gradients, measuring the spectrum of the motional impedance amplitude for each sample. According to step S2, the standard viscosity liquid sample is obtained. The dynamic viscosity is taken as the dynamic viscosity of the standard viscosity liquid sample. The value of is used to obtain the dynamic viscosity. With normalized damping coefficient The linear regression results, the slope of the linear regression equation is the scaling coefficient. The intercept of the linear regression equation is the scaling coefficient. scaling factor scaling factor It was determined through experiments that... It was also measured experimentally; S4: Transfer the parameters obtained in step S2 and and the scaling coefficients obtained in step S3 and Substitute into step S1 as well as The energy storage modulus is calculated from the expression. Dynamic viscosity and equivalent load quality .

[0007] Further, in step S2, according to The least squares optimization model for the spectrum is established as follows: exist In a single measurement of the spectrum, the model parameters are assumed to be... and Keep constant, angular frequency For measurement The experimental condition variables, using Representing discrete experimental conditions, Discrete time Represented as ,but and The relationship can be represented as , In the formula, Error term; model function Defined as ; Error term It follows a Gaussian distribution with zero mean and a standard deviation of . The model parameter vector is represented as According to The distribution characteristics can be used to obtain a specific model parameter vector. corresponding probability density for ; for M Experimental conditions ,all joint probability density For all The product of, i.e. ; The goal of least squares is to make Maximize, make Minimal model parameter vector This is the least squares optimal solution, therefore the least squares optimization model can be expressed as: ; In the formula, The weights are determined by different experimental conditions. Standard deviation of the corresponding measured values It has been determined.

[0008] Furthermore, in step S2, finding the initial values ​​of the model parameter vector specifically involves: Within the sensor's operating frequency range Total impedance of the coil The impact is relatively small, therefore it is ignored. Item, obtained ; In the formula, The DC resistance of the coil wire is... , ; Able to be maximum value It means, i.e., the following formula ; neglect At angular frequency place, Find the maximum value ,use The maxima of the spectrum and the angular frequency at those points can be used to obtain... and The value, Further calculations yielded Then, solve the following system of equations. ; The solution to this system of equations is the model vector. The initial value of .

[0009] Furthermore, calculations yielded... Specifically: Determine the impedance amplitude Maximum value and the angular frequency here Using DC resistance and ,calculate ; exist On the curve, determine frequency points ; calculate , .

[0010] Furthermore, in step S2, the various experimental conditions are determined. The corresponding weights are as follows: Least square fitting is performed using equal weights; Calculate the deviation of the equal weight estimate; Weight estimation.

[0011] Furthermore, the least squares fitting using equal weights is specifically as follows: make That is, assigning equal weights to each measured value. , with model vector Nonlinear least squares fitting is performed on the initial values ​​to obtain the estimated model parameters. .

[0012] Furthermore, the specific deviation in calculating the equal-weighted estimate is as follows: Model parameter estimates Substitute into the model function ,get The estimated value ,calculate Measured values and Deviation between .

[0013] Furthermore, the weight estimation steps are as follows: Using a window width of rectangular window right Cut off the section, and the resulting length is The standard deviation of the sequence is This standard deviation is assigned to the measurement variable at the center of the rectangular window, thus obtaining the weight at the center of the window. for By sequentially changing the center position of the rectangular window and sliding it along the experimental condition variable axis, each... corresponding weights .

[0014] Further, in step S3, Let be the electromechanical coupling coefficient of the sensor, which is a constant. The coefficient is the square of the electromechanical coupling coefficient. The calculation process is as follows: A mass of [value] is loaded onto the sensor probe. The load was measured to obtain at least three different angular frequencies of the sensor coil. Corresponding motional impedance amplitude The data will include at least three and the corresponding Data substitution Calculate and ; A mass of [value] is loaded onto the sensor probe. The load, Not equal to At least three different angular frequencies of the sensor coil were measured. Corresponding motional impedance amplitude The data will include at least three and the corresponding Data substitution The model parameter identification method is used to calculate and ; Will M m1 , M m2 , M m_n1 as well as M m_n2 Substitution The coefficients were calculated. .

[0015] Furthermore, in step S3, the initial equivalent mass The total equivalent elastic modulus of the two springs of the sensor The results were obtained through experiments, specifically: When there is no measurement sample, i.e., the sensor probe is only in contact with air, at least three different angular frequencies of the sensor coil are measured. Corresponding motional impedance amplitude The data will include at least three and the corresponding Data substitution The model parameter identification method is used to calculate and ; Will and coefficients Substitution Calculations yielded and Since the probe is not in contact with the sample being measured at this time, therefore... They are respectively equal to and .

[0016] Compared to existing technologies, the method for measuring the dynamic viscosity, storage modulus, and equivalent load mass of blood samples in this invention establishes an equivalent model of the mechanical vibration system of a blood viscoelastic sensor during operation, thereby obtaining the dependence of model parameters on the dynamic viscosity, storage modulus, and equivalent load mass of the sample. It then establishes an equivalent circuit for the coil in the sensor, derives the expression for the motional impedance mode of the coil based on the equivalent circuit, and identifies the model parameters using the spectral data of the motional impedance mode through a model parameter identification method. and Experiments were conducted using standard viscosity liquid samples with multiple gradients to obtain calibration coefficients. The dynamic viscosity was then calculated based on the identified model parameters and the calibration coefficients. Energy storage modulus and equivalent load quality Through the above steps, the dynamic viscoelasticity and equivalent load mass of the sample during the coagulation process can be measured simultaneously. Attached Figure Description

[0017] Figure 1 This is a three-dimensional view of an existing thromboelasticity detection sensor in the background art; Figure 2 This is a flowchart of the method for measuring the dynamic viscosity, storage modulus, and equivalent load mass of blood samples according to the present invention. Figure 3 This is a schematic diagram of the equivalent model of the mechanical vibration system of the viscoelastic sensor in this invention; Figure 4 This is the equivalent circuit diagram of the viscoelastic sensor coil in this invention; Figure 5 This is a diagram showing the amplitude-frequency characteristic of the motional impedance of the viscoelastic sensor coil in this invention. Figure 6 This is a diagram showing the dynamic impedance phase frequency characteristic of the viscoelastic sensor coil in this invention; Figure 7 The actual measured values ​​of the motional impedance mode and their weighted fitting plot are shown. Figure 8 A graph showing the measured and estimated standard deviations of the motional impedance modulus; Figure 9The graph shows the weight allocation results for the nonlinear least squares fitting. Figure 10 This is the result of dynamic viscosity calibration; Figure 11 Thromboelastography signal diagrams for two thromboelastography quality control samples; Figure 12 Dynamic viscosity graphs of two thromboelastography quality control samples; Figure 13 Storage modulus diagrams for two thromboelastography quality control samples; Figure 14 Equivalent load mass diagrams for two thromboelastography quality control samples; Figure 15 This is a thromboelastic signal map of a whole blood sample. Figure 16 This is a dynamic viscosity graph of a whole blood sample. Figure 17 Storage modulus diagram of whole blood sample; Figure 18 This is an equivalent load mass map of whole blood samples. Detailed Implementation

[0018] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0019] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains. The terminology used herein in the description of the invention is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. The term "and / or" as used herein includes any and all combinations of one or more of the associated listed items.

[0020] Figure 2 This is a flowchart of the method for measuring the dynamic viscosity, elasticity, and equivalent loading mass of blood samples according to the present invention. The specific method for measuring the dynamic viscosity, elasticity, and equivalent loading mass of blood samples according to the present invention is as follows: 1.1 Storage modulus and dynamic viscosity

[0021] Before coagulation, blood viscosity dominates, and its response to shear force is essentially permanent deformation. As blood begins to coagulate, the elastic effect gradually increases, and the deformation caused by shear force tends to be recoverable. This invention discusses the dynamic viscoelasticity of blood. The mechanical response characteristics of a material under harmonic strain or stress are called the dynamic viscoelasticity of the material. The elastic and viscous characteristics of a material can be obtained simultaneously through dynamic viscoelasticity testing. In dynamic viscoelasticity testing, a small-amplitude harmonic shear flow field is used, reflecting the linear viscoelastic characteristics of the tested material.

[0022] Let the small-amplitude harmonic strain acting on the blood sample be... ; In the formula, ω is the angular frequency; t is time; , is the imaginary unit; Let be the amplitude of the strain. If the blood sample is considered a linear body, then its harmonic stress and strain have the same frequency. The harmonic stress within the sample can be expressed as... ; In the formula, The magnitude of the stress; This represents the phase difference between stress and strain. Therefore, It can be further expressed as ; In the formula, and Defined by the following two formulas respectively ; ; The storage modulus of the sample represents the contribution of elasticity. The dynamic viscosity of the sample represents the contribution of viscosity. 1.2 Equivalent Model of Vibration System

[0023] When the sensor probe is immersed in a blood sample, the movement of the probe can be used to... Figure 3 The single-degree-of-freedom second-order damped equivalent model is shown. The velocity field phasor of the sample inside the measuring cup... V s The following passive wave equation is satisfied ; In the formula, For the Laplace operator; k The complex wave number of a shear wave in a viscoelastic medium is defined by the following formula: ; In the formula, The density of the sample being tested.

[0024] operating frequency of viscoelastic sensor ω The value is relatively low, which can be assumed that the radial dimension of the sample is much smaller than the wavelength of the shear wave in the sample. Therefore, the equation... The wave equation satisfies the quasi-static approximation conditions. The solution equation under the quasi-static conditions is... From the wave equation, we can obtain Figure 3 The spring constant of an effective spring Damping coefficient of equivalent damper They are respectively ; In the above two formulas, and These represent the total equivalent elastic coefficient and total damping coefficient of the two reeds in the vibration viscoelastic sensor, respectively. This represents the radiation resistance when the two reeds of a vibratory viscoelastic sensor radiate a sound field. Let be a constant determined by the geometry of the measuring cup and probe. Furthermore, Figure 3 The mass of the medium-efficiency mass block M m Can be written as ; In the formula, This represents the additional radiative mass when the two reeds of a vibratory viscoelastic sensor radiate a sound field. This represents the sum of the probe's own mass and the equivalent mass of the vortex reed. The equivalent load mass of the sample being tested.

[0025] according to Figure 3 The probe motion equation based on phasor representation can be obtained as follows: ; In the formula, The phasor of the probe velocity; The phasor of the driving force on the probe is provided by the Lorentz force on the coil, as expressed in the following expression. ; In the formula, I c The phasor of the current in the coil; the electromechanical coupling coefficient of the sensor. Defined by the following formula (12); In the formula, A conductor vector element of a coil; It is the magnetic flux density vector; Represent the geometry of the closed loop of the coil; 1.3 Motional Impedance of the Coil When a time-harmonic current flows through the coil of the viscoelastic sensor, the resulting harmonic Lorentz force drives the coil, producing harmonic motion, which in turn causes the sensor's probe to move synchronously. The probe interacts with the sample being measured, and its motion is influenced by the mechanical properties of the sample. Since the coil and probe are rigidly connected, their velocity phasor in the magnetic field is also... Then the phasor of the induced electromotive force in the coil can be obtained. for ; Changes in the induced electromotive force will lead to changes in the equivalent impedance of the coil. In summary, changes in the mechanical properties of the sample will modulate the equivalent impedance of the coil.

[0026] Since the sensor operates at a low frequency, the eddy current losses in the coil can be ignored. When considering the equivalent circuit of the coil, the equivalent resistance representing the eddy current losses in the high-frequency region can be neglected; only the DC resistance of the coil wire needs to be considered. coil inductance , and style The motional electromotive force represented The influence of small signals. Under the action of small signals, vibration sensors can be regarded as lumped parameter linear systems, so the equivalent circuit of the coil can be used. Figure 4 express. Figure 4 In, equivalent circuit elements and The values ​​are respectively ; ; ; in the formula Represents coefficients The square of.

[0027] Figure 4 middle, The component of the coil's equivalent impedance affected by the induced electromotive force is called motional impedance. The expression is as follows ; In the formula, the third term on the right is the motional impedance of the coil. , ; The modulus and phase angle are respectively ; ; Their frequency characteristics are respectively shown in Figure 5 as well as Figure 6 . At angular frequency The phase at that point is zero, and its magnitude reaches a maximum. . The expression is ; The measured coil impedance Subtract the DC resistance of the coil and resistance We obtain, that is, calculate using the following formula. . 1.4 Dynamic Viscoelasticity and Equivalent Load Mass Detection Method Based on Parameter Identification of Motion Impedance Model

[0028] Will and relative constant Perform normalization, let ; Substituting the above three equations into the equation ,but Can be rewritten as ; From the formula visible, The spectrum is determined by a specific set of model parameters. and Uniquely determined. In an ideal situation, if three different angular frequencies are known... place The value, substituted into the formula (26) We obtain three equations. Solving the system of equations formed by these three equations will yield the uniquely determined model parameters. and However, the actual measurements obtained... Inevitably contains various errors, determined by a limited set of three data points. The accuracy of model parameters is difficult to guarantee. To reduce the impact of random errors in measurement data, it is necessary to establish model parameter estimates with better statistical performance based on a large amount of measurement data. The number of linear independent equations obtained in this way is much larger than the number of undetermined model parameters, which is known as the "overdetermined problem." Utilizing... Within a certain range By using the spectral data to establish an overdetermined system of equations and identify the model parameters, relatively accurate model parameters can be obtained. , and .

[0029] Three normalized model parameters were obtained using the model parameter identification method. and Then, substituting into equations (7), (8), and (9) respectively, we can obtain... ; ; ; The correlation coefficients in the above three equations are determined by the following equations. ; ; ; . 1.5 Parameter Identification of Motion Impedance Model Based on Least Squares Fitting

[0030] The model structure of motional impedance is known, and the identification of its model parameters falls under the category of parametric model identification problems in modern identification methods. This parametric model identification problem is solved by minimizing the error criterion function between the model and the measured data. Modern identification methods, in terms of their basic principles, can be divided into three types: least squares identification methods, gradient correction identification methods, and probability density approximation identification methods. The least squares method, among the least squares identification methods, is the most fundamental, its related theory is well-developed, and its application is the most widespread. The least squares method is adopted here. 1.5.1 The model is established using the least squares method.

[0031] exist In a single measurement of the spectrum, the model parameters can be considered as... and Keep constant. Angular frequency ω For measurement The experimental condition variables, using Represents discrete experimental conditions. Discrete time Represented as ,but and The relationship can be represented as ; In the formula, the model function Defined as ; The least squares method is a special case of the more universal maximum likelihood method. When applying the maximum likelihood method, the main focus is on obtaining the measured values ​​using the estimated model parameters. The probability of the error term, not the probability of the model parameter estimates being correct. It follows a Gaussian distribution with zero mean and a standard deviation of . The model parameter vector is represented as Then according to The distribution characteristics can be used to obtain a specific model parameter vector. corresponding probability density for ; for M Experimental conditions ,all joint probability density For all The product of, i.e. ; The goal of least squares is to make Maximize. From equation (37), we know that... Minimal model parameter vector This is the least squares optimal solution. Therefore, the least squares optimization model can be expressed as: ; In the formula, the weights The weights are determined by different experimental conditions. Standard deviation of the corresponding measured values What has been determined, namely ; The essence of the least squares optimization model represented by equation (38) is to find the model parameter vector. This minimizes the weighted sum of squares of the theoretical dynamic impedance amplitude determined by it and the residual of the measured value.

[0032] Model function It's about model parameters. Nonlinear functions. To handle this type of nonlinear least squares problem, it is necessary to start from... Starting from a certain initial value, iterative methods including Gauss-Newton, gradient descent, and Levenberg-Marquardt are used to find the error surface. The global minimum point on.

[0033] When applying the least squares method to solve specific engineering problems, the determination of the initial fitting values ​​and the estimation of the weights have a significant impact on the fitting effect. 1.5.2 Initial value estimation of model parameters

[0034] Using iterative methods to find error surfaces When the global minimum point is reached, the model parameter vector is correctly estimated. The initial values ​​are particularly important. Reasonable initial values ​​can not only prevent the iterative process from converging to local minima on the error surface, but also reduce the number of iterations and improve computational efficiency. It is essential to ensure that the model parameter vectors... The initial value should be as close as possible to the global minimum point. The following method is used for initial value estimation.

[0035] Within the operating frequency range of the sensor, in equation (17) For total impedance The impact is relatively small. A rigorous, precise solution is not required when determining the initial values ​​of the model parameters. Therefore, for equation (17), the effect can be ignored. Item, rewrite it as ; In the formula, The expression is ; set up Substituting into equation (40), we can obtain ; According to equation (42), we can obtain ; From equation (43), it can be seen that for any If satisfied Then the following formula holds true. ; In the formula, , .Will , Substituting into equation (43) and using equation (44), we can obtain ; Solving equation (45) yields... ; Specifically, take Then equation (46) can be simplified to ; When ignored hour, can be maximum value It means, i.e., the following formula ; Therefore The following formula can be used to calculate ; Based on the above analysis, and after performing impedance analysis on the coil and measuring its DC resistance and AC impedance, the following steps can be used to solve the problem. .

[0036] Step 1 Solve Z mr , ω 0: That is, determine the impedance amplitude | Z (j ω )|Maximum Z mr and the angular frequency here ω 0; Step 2 Solve r 0: Using DC resistance R e and Z mr ,calculate r 0= Z mr / R e ; Step 3 Solve ω 1. ω 2: In | Z (j ω On the curve, determine what makes | Z (j ω 1)|= | Z (j ω 2)|= r 0 1 / 2 R e frequency points ω 1. ω 2; Step 4 Calculation Q ms : Q ms= ω 0 r 0 1 / 2 / | ω 2− ω 1|.

[0037] Calculated Then, combined with previously obtained information and Based on equations (21), (41), and (48), the following system of equations can be established. ; The solution to this system of equations can be used as a model vector. The initial value of . 1.5.3 Weighting of Motion Impedance Amplitude Measurements

[0038] In the model function Before performing nonlinear least squares fitting, it is also necessary to determine the various experimental conditions. The corresponding weights. When the reliability of the measured value is high (i.e., the standard deviation). When the value is relatively small, a higher weight is assigned to it; conversely, a lower weight is assigned to it. Because... It has non-flat frequency characteristics, for Measurements are typically performed with varying precision. Furthermore, changes in the mechanical properties of blood samples during the coagulation process lead to… Due to the time-varying nature of the frequency, it is impossible to obtain sufficient sample size and prior knowledge of probability distribution for the measured values ​​under the same experimental conditions in a single frequency sweep.

[0039] for Unequal precision measurements, optimal weights Should be with Related variables. During a single frequency sweep, to shorten the measurement time, for each angular frequency... Only one measurement .Depend on The standard deviation cannot be directly derived from a single sample. Statistical information. Furthermore, during coagulation measurements, due to the model parameter vector... Since it is a time variable, therefore The inability to predict in advance, and therefore the inability to be determined by Prior knowledge estimation of probability distributions These factors all increase the difficulty of weight estimation. In many applications, it is often simply assumed that... We assign equal weights to each measurement value. However, this may result in a poor fit.

[0040] The weighting estimation of the dynamic impedance amplitude measurement is based on the following idea: within a relatively narrow frequency band, the sweep frequency experimental conditions can be considered similar, thus within this frequency band... The standard deviations should also be relatively close; if there is enough measurement data within the frequency band, the standard deviation at the center frequency can be expressed using the standard deviations of all measurement data within that frequency band. The specific steps of this method are as follows: (1) Use equal weights for least squares fitting make That is, assigning equal weights to each measured value. Using the results of the initial value estimation method as initial values, least squares fitting is performed to obtain the estimated values ​​of the model parameters. Although this parameter estimate may not be entirely accurate, it can at least be assumed that its deviation from the accurate value will not be too large.

[0041] (2) Calculate the deviation of the equal weight estimate First, the model parameter estimates obtained by fitting with equal weights in step (1) are... Substituting into equation (35), we get The estimated value ; Next, calculate Measured values and Deviation between ; (3) Weight estimation When the sweep step size is small, for a continuous range of measurements, the aforementioned requirements for similar experimental conditions can be considered satisfied. The center position is as follows: The window width is rectangular window ; right Cut off the section, and the resulting length is The standard deviation of the sequence is ; Assign this standard deviation to the measurement variable at the center of the rectangular window to obtain the weight at the center of the window. for ; By sequentially changing the center position of the rectangular window and sliding it along the experimental condition variable axis, each... corresponding weights .

[0042] Frequency sweep of a sensor (start and end frequencies are respectively) and Experimental conditions The step size is Applying the above weight estimation method to the obtained measurement data, a window width of 11 (e.g.) is taken. Figure 7 (As shown). The obtained individual The standard deviation estimate at [location] is shown in [reference]. Figure 8 For ease of comparison, the standard deviations of the measured data at several discrete angular frequencies are presented together. The measured values ​​of the standard deviations at these angular frequencies are in good agreement with the estimated values, thus verifying the effectiveness of this weight estimation method. The corresponding estimated weights are as follows: Figure 9 As shown, in frequency bands far from natural frequencies, the measurement accuracy is higher, resulting in larger weights. 1.5.4 Model Parameter Identification

[0043] After solving the two key problems of initial parameter estimation and weight estimation, the weighted least squares fitting method can be used to identify the model parameters. Specifically: Step 1: Based on the impedance amplitude |Z (j ω | curve, solve for natural frequency ω 0. Maximum impedance amplitude Z mr and mechanical quality factor Q ms Solve the simultaneous equations to obtain the initial values ​​of the model parameters; Step 2: Using the estimated values ​​from Step 1 as initial values, perform equal-weighted fitting and calculate the deviation of the equal-weighted estimation; Step 3: Apply the sliding piecewise weight estimation method to estimate the weights based on the deviation of the equal weight estimation; Step 4: Using the result of the equal-weight fitting in step 2 as the initial value, perform weighted fitting using the weight estimation result in step 3 to obtain the final model parameter estimation result.

[0044] In step 4, the initial values ​​of the weighted fitting parameters do not use the initial value estimation results from step 1. Instead, they use the results of the equal-weighted fitting from step 2 as the initial values. The initial values ​​of the parameters obtained in step 1 are only used as the initial values ​​for the equal-weighted fitting in step 2. The reason for this approach is that experiments have shown that the error of the equal-weighted fitting results is smaller than the error of the initial value estimation, especially when the frequency sweep step size is large. 1.6 Solving for the coefficients of the scaling equation

[0045] Energy storage modulus Dynamic viscosity and equivalent load mass The three normalized model parameters obtained from model parameter identification are compared with those obtained from model parameter identification. and Linear correlation. (This needs to be considered...) and To perform calibration, it is necessary to determine the coefficients in equations (27), (28), and (29). , , and .

[0046] 1.6.1 Calibration equation for dynamic viscosity right The scaling requires determining the coefficients in equation (28). and Calibration is performed using a standard viscosity fluid. In most common applications, the standard viscosity fluid can be considered a Newtonian fluid.

[0047] The first step involves taking standard viscosity liquid samples of multiple gradients for experiments and measuring the spectrum of the motional impedance amplitude corresponding to each sample. And by applying the above-mentioned method for identifying motional impedance model parameters, the following results were obtained: For example, the parameters of the standard viscosity liquid used in the experiment are shown in Table 1. Experiments were conducted on samples spl. 1 to spl. 5. The standard viscosity liquid was maintained at its set temperature of 20 °C using a temperature control device. After the temperature stabilized for 5 minutes, the motional impedance spectrum of the voice coil was measured, and model parameters were estimated. To reduce the influence of random errors in sample loading on the calibration results, the experiments were repeated 5 times for spl. 1 to spl. 5, and the model parameters were... The estimation results are shown in Table 2.

[0048] Table 1. Parameters of Standard Viscosity Fluid for Calibration

[0049] Table 2. Normalized damping coefficients obtained from five repeated experiments of samples spl. 1 to spl. 5. R m_n

[0050] Table Notes: R m_n The unit is

[0051] The second step is to use the dynamic viscosity of the standard viscosity liquid sample as the dynamic viscosity in equation (28). The value of the normalized damping coefficient By taking the average value of multiple experiments and using data from multiple standard viscosity liquid samples, a linear fit can be performed to obtain the coefficients in equation (28). , For example, using the dynamic viscosity in Table 1 and the five experiments in Table 2... By fitting the average value, we can obtain... Figure 10 The dynamic viscosity shown With normalized damping coefficient The linear regression results are given by the corresponding calibration equation (the units of the quantities in the equation are in SI units). ; 1.6.2 Calibration equation for elastic storage modulus Because it is difficult to obtain standard materials similar to those used in dynamic viscosity calibration, and due to differences in testing conditions, the test results are also difficult to compare with those obtained from third-party rheometers and other equipment. Therefore, the calibration of elastic storage modulus cannot be performed using standard materials or by comparing with third-party instruments. Here, we utilize existing results from viscosity calibration and measured sensor data. Bl The coefficients are obtained by indirectly solving the coefficients of the elastic energy storage modulus calibration equation.

[0052] First, examining equations (27) and (28) reveals that... Calibration equation coefficientsa The coefficients are the same as those of the first-order term in the viscosity scaling equation. a The value was obtained during dynamic viscosity calibration.

[0053] Secondly, it is only necessary to determine Using equations (30) and (31), we can obtain ; The equivalent elastic modulus of the vibrating spring Sensors Bl The coefficients can be measured experimentally, and they are summed. a Substituting all the results into equation (57), we can obtain .

[0054] coefficient The calculation process is as follows: A mass of [value] is loaded onto the sensor probe. The load was measured to obtain at least three different angular frequencies of the sensor coil. Corresponding motional impedance amplitude The data will include at least three and the corresponding Data substitution Calculate and ; A mass of [value] is loaded onto the sensor probe. The load, Not equal to At least three different angular frequencies of the sensor coil were measured. Corresponding motional impedance amplitude The data will include at least three and the corresponding Data substitution The model parameter identification method is used to calculate , and ; Will M m1 , M m2 , M m_n1 as well as M m_n2 Substitution The coefficients were calculated. .

[0055] The total equivalent elastic modulus of the two springs of the sensor The results were obtained through experiments, specifically: When there is no measurement sample, i.e., the sensor probe is only in contact with air, at least three different angular frequencies of the sensor coil are measured. Corresponding motional impedance amplitude The data will include at least three and the corresponding Data substitution The model parameter identification method is used to calculate and ; Will and coefficients Substitution Calculations yielded Since the probe is not in contact with the sample being measured at this time, therefore... equal .

[0056] For example, for the same sensor used in the above dynamic viscosity calibration, its measured value is... The coefficient is 8.1465 Web∙m -1 Equivalent elastic modulus of the vibrating spring It is 522.606 kg·s -2 The storage modulus of the sample can be obtained. Relative normalized equivalent elasticity coefficient The scaling equation is (the dimensions of the quantities in the equation are in SI units). ; 1.6.3 Calibration equation for equivalent load mass When the sensor When the coefficients have been measured, then equation (29) regarding The calibration equations only need to determine the initial equivalent mass of the vibration system. The equivalent elastic modulus of the spring. Sensors Bl Similar coefficients, initial equivalent mass It can also be measured experimentally.

[0057] Initial equivalent mass The results were obtained through experiments, specifically: When there is no measurement sample, i.e., the sensor probe is only in contact with air, at least three different angular frequencies of the sensor coil are measured. Corresponding motional impedance amplitude The data will include at least three and the corresponding Data substitution The model parameter identification method is used to calculate and ; Will and coefficients Substitution Calculations yielded Since the probe is not in contact with the sample being measured at this time, therefore... equal .

[0058] For example, for the same sensor mentioned above, its measurement It is 1.10611×10 -3 kg, then the equivalent load mass of the sample can be obtained. Relative normalized equivalent quality The scaling equation is . 1.7 Results of dynamic viscoelasticity and equivalent load mass tests during the coagulation process

[0059] Applying the aforementioned dynamic viscoelasticity and equivalent load mass detection methods based on kinetic impedance model parameter identification, experiments were conducted on two different thromboelastography quality control samples (Low-value QC and High-value QC, mainly composed of sodium citrate anticoagulated porcine plasma) at different thromboelastography maximum amplitude levels. The results were obtained... Figures 11 to 14 The results, obtained from experiments on whole blood samples from healthy volunteers, showed that... Figures 15 to 18 The result.

[0060] The present invention relates to a method for measuring the dynamic viscosity, storage modulus, and equivalent loading mass of blood samples. By establishing an equivalent model of the mechanical vibration system of a blood viscoelastic sensor during operation, the dependence of model parameters on the dynamic viscosity, storage modulus, and equivalent load mass of the sample was obtained. An equivalent circuit of the coil in the sensor was established, and based on this circuit, the expression for the motional impedance mode of the coil was derived. Using the spectral data of the motional impedance mode, the model parameters were identified through a model parameter identification method. and Experiments were conducted using standard viscosity liquid samples with multiple gradients to obtain calibration coefficients. The dynamic viscosity was then calculated based on the identified model parameters and the calibration coefficients. Energy storage modulus and equivalent load quality Through the above steps, the dynamic viscoelasticity and equivalent load mass of the sample during the coagulation process can be measured simultaneously, which expands the application range of the blood viscoelasticity detection system, changes the status quo that most instruments can only detect a single parameter, and provides the possibility of comprehensively evaluating coagulation function based on more parameters.

[0061] The above embodiments merely illustrate several implementation methods of the present invention, and their descriptions are relatively specific and detailed, but they should not be construed as limiting the scope of the invention patent. It should be noted that, for those skilled in the art, several modifications and improvements can be made without departing from the concept of the present invention. These are all equivalent modifications and improvements made to the above embodiments based on the essential technology of the present invention, and all of these fall within the protection scope of the present invention.

Claims

1. A method for measuring the dynamic viscosity, storage modulus, and equivalent loading mass of a blood sample, characterized in that, Includes the following steps: S1: Establish an equivalent model of the mechanical vibration system of the blood viscoelastic sensor during operation. In the equivalent model... In the formula, The spring constant of the equivalent spring. This is the total equivalent elastic coefficient of the sensor reed; The storage modulus of the sample; It is a constant determined by the geometry of the measuring cup and the probe; The damping coefficient of the equivalent damper; This represents the total damping coefficient of the sensor reeds; Indicates the radiation resistance when the reed radiates a sound field; The dynamic viscosity of the sample; The mass of the equivalent mass block; This represents the additional radiative mass when the sensor reed radiates the sound field. This represents the sum of the probe's own mass and the equivalent mass of the reed. The equivalent loading mass of the sample being tested is... and relative constant Normalize, Let be the electromechanical coupling coefficient of the blood viscoelastic sensor, and let From the above formula, we can obtain , In the formula, the coefficients and The expressions are respectively ; S2: Establish the equivalent circuit of the coil in the sensor, based on the equivalent circuit... The motional impedance of the coil , Angular frequency, The imaginary unit; The model is Normalized ,and Substitution get ,according to To establish a least-squares optimization model based on the spectrum, initial values ​​for the model parameter vector and determination of various experimental conditions are needed. The corresponding weights are used to perform nonlinear least squares fitting based on the parameter vector and the weights to obtain the parameters. and ; S3: Experiments were conducted using standard viscosity liquid samples with multiple gradients, measuring the spectrum of the motional impedance amplitude for each sample. According to step S2, the standard viscosity liquid sample is obtained. The dynamic viscosity is taken as the dynamic viscosity of the standard viscosity liquid sample. The value of is used to obtain the dynamic viscosity. With normalized damping coefficient The linear regression results, the slope of the linear regression equation is the scaling coefficient. The intercept of the linear regression equation is the scaling coefficient. scaling factor scaling factor It was determined through experiments that... It was also measured experimentally; S4: Transfer the parameters obtained in step S2 and and the scaling coefficients obtained in step S3 and Substitute into step S1 as well as The energy storage modulus is calculated from the expression. Dynamic viscosity and equivalent load quality .

2. The method for measuring the dynamic viscosity, storage modulus, and equivalent loading mass of blood samples according to claim 1, characterized in that: In step S2, according to The least squares optimization model for the spectrum is established as follows: exist In a single measurement of the spectrum, the model parameters are assumed to be... and Keep constant, angular frequency For measurement The experimental condition variables, using Representing discrete experimental conditions, Discrete time Represented as ,but and The relationship can be represented as ， In the formula, For error terms; model function Defined as ； Error term It follows a Gaussian distribution with zero mean and a standard deviation of . The model parameter vector is represented as According to The distribution characteristics can be used to obtain a specific model parameter vector. corresponding probability density for ; for M Experimental conditions ,all joint probability density For all The product of, i.e. ; The goal of least squares is to make Maximize, make Minimal model parameter vector This is the least squares optimal solution, therefore the least squares optimization model can be expressed as: ； In the formula, The weights are determined by different experimental conditions. Standard deviation of the corresponding measured values It has been determined.

3. The method for measuring the dynamic viscosity, storage modulus, and equivalent loading mass of blood samples according to claim 2, characterized in that: In step S2, finding the initial values ​​of the model parameter vector specifically involves: Within the sensor's operating frequency range Total impedance of the coil The impact is relatively small, therefore it is ignored. Item, obtained , In the formula, The DC resistance of the coil wire is... , , ; Able to be maximum value It means, i.e., the following formula ; neglect At angular frequency place, Find the maximum value ,use The maxima of the spectrum and the angular frequency at those points can be used to obtain... and The value, Further calculations yielded Then, solve the following system of equations. ； The solution to this system of equations is the model vector. The initial value of .

4. The method for measuring the dynamic viscosity, storage modulus, and equivalent loading mass of blood samples according to claim 3, characterized in that: Calculated Specifically: Determine the impedance amplitude Maximum value and the angular frequency here Using DC resistance and ,calculate ; exist On the curve, determine frequency points ; calculate , .

5. The method for measuring the dynamic viscosity, storage modulus, and equivalent loading mass of blood samples according to claim 3, characterized in that: In step S2, the experimental conditions are determined. The corresponding weights are as follows: Least square fitting is performed using equal weights; Calculate the deviation of the equal weight estimate; Weight estimation.

6. The method for measuring the dynamic viscosity, storage modulus, and equivalent loading mass of blood samples according to claim 5, characterized in that: The specific steps for using equal weights for least squares fitting are as follows: make That is, assigning equal weights to each measured value. , with model vector Nonlinear least squares fitting is performed on the initial values ​​to obtain the estimated model parameters. .

7. The method for measuring the dynamic viscosity, storage modulus, and equivalent loading mass of blood samples according to claim 6, characterized in that: The specific deviation in calculating the equal weight estimate is as follows: Model parameter estimates Substitute into the model function ,get The estimated value ,calculate Measured values and Deviation between .

8. The method for measuring the dynamic viscosity, storage modulus, and equivalent loading mass of blood samples according to claim 7, characterized in that: The specific steps for weight estimation are as follows: Using a window width of rectangular window right Cut off, the resulting length is The standard deviation of the sequence is This standard deviation is assigned to the measurement variable at the center of the rectangular window, thus obtaining the weight at the center of the window. for By sequentially changing the center position of the rectangular window and sliding it along the experimental condition variable axis, each... corresponding weights .

9. The method for measuring the dynamic viscosity, storage modulus, and equivalent loading mass of blood samples according to claim 1, characterized in that: In step S3, Let be the electromechanical coupling coefficient of the sensor, which is a constant. The coefficient is the square of the electromechanical coupling coefficient. The calculation process is as follows: A mass of [value] is loaded onto the sensor probe. The load was measured to obtain at least three different angular frequencies of the sensor coil. Corresponding motional impedance amplitude The data will include at least three and the corresponding Data substitution Calculate and ; A mass of [value] is loaded onto the sensor probe. The load, Not equal to At least three different angular frequencies of the sensor coil were measured. Corresponding motional impedance amplitude The data will include at least three and the corresponding Data substitution The model parameter identification method is used to calculate and ; Will M m1 , M m2 , M m_n1 as well as M m_n2 Substitution The coefficients were calculated. .

10. The method for measuring the dynamic viscosity, storage modulus, and equivalent loading mass of blood samples according to claim 9, characterized in that: In step S3, the initial equivalent mass The total equivalent elastic coefficient of the two reeds of the sensor The results were obtained through experiments, specifically: When there is no measurement sample, i.e., the sensor probe is only in contact with air, at least three different angular frequencies of the sensor coil are measured. Corresponding motional impedance amplitude The data will include at least three and the corresponding Data substitution The model parameter identification method is used to calculate and ; Will and coefficients Substitution Calculations yielded and Since the probe is not in contact with the sample being measured at this time, therefore... They are respectively equal to and .

Images