Multi-organ arterial critical closing pressure synchronous monitoring device, apparatus and operating method

Abstract

This invention discloses a device, equipment, and operating method for synchronous monitoring of critical closure pressure in multiple organs' arteries. The device includes: a waveform acquisition module for acquiring synchronously collected radial artery pressure waveforms and arterial blood flow velocity waveforms from multiple organs; a data cleaning module for cleaning the radial artery pressure waveforms and arterial blood flow velocity waveforms from multiple organs; a feature recognition module for determining the rising and falling branches of the radial artery pressure waveform and the arterial blood flow velocity waveform of each organ; and a linear regression calculation module for performing linear regression calculations on the rising or falling branch of the arterial blood flow velocity waveform of each organ and the rising or falling branch of the radial artery pressure waveform, respectively. The blood pressure value at which the corresponding regression line velocity of each organ is zero is the real-time critical closure pressure of that organ. This invention can obtain the critical closure pressure of multiple organs without pre-setting organ perfusion pressure values, largely avoiding human error.

Description

Technical Field

[0001] This application relates to the field of medical technology, and in particular to a device, equipment, and operating method for synchronous monitoring of critical closure pressure in multiple organ arteries. Background Technology

[0002] As arterial blood pressure progressively decreases until blood flow ceases, the arterial pressure remains higher than the venous blood pressure. As the name suggests, the arterial blood pressure at which blood flow stops is called the critical closing pressure (CCP) or zero flow pressure. Different organs determine and regulate their CCPs differently, meaning that perfusion to different organs varies under hypotension. Therefore, understanding the CCPs of different organs allows us to identify perfusion pressure differences between organs, thereby optimizing resuscitation blood pressure targets during shock treatment, ensuring adequate systemic organ perfusion, and optimizing hemodynamic management during shock.

[0003] Currently, there are no validated and feasible methods in clinical practice to simultaneously monitor critical closure pressures in multiple organs and the state of organ vascular autoregulation. Blood pressure targets for shock resuscitation remain at the stage of empirical treatment. Therefore, it is extremely important to develop tools and methods for simultaneous monitoring of critical closure pressures in multiple organs that can be widely accepted in clinical practice.

[0004] For determining the critical closure pressure of a single organ, a widely used method is transcranial Doppler ultrasound (TCD) to calculate the CCP of the brain. This method first acquires invasive arterial blood pressure waveforms and bilateral middle cerebral artery blood flow waveforms, performing analog-to-digital conversion and clock synchronization. Then, the intercept point of the regression line between the single arterial blood pressure plotted along the X-axis and the middle cerebral artery blood flow velocity (FV) plotted along the Y-axis is used to estimate the CCP. Based on this, there are alternative methods using the first harmonic ratio of the FV pulse and the ABP pulse.

[0005] The aforementioned methods, such as estimating the intercept point of the regression line between a single arterial blood pressure plotted along the X-axis and the middle cerebral artery blood flow velocity (FV) plotted along the Y-axis, or the first harmonic ratio method, all rely on regressing blood pressure and blood flow waveforms at sampling rates above 100 Hz to obtain the critical pressure occlusion (CCP). These methods for calculating intracranial CCP require a pre-assumption of intracranial pressure of 12 mmHg, which may lead to biased results and mislead clinical treatment. Furthermore, these methods can only be used for measuring the critical closure pressure of cerebral vessels and cannot be applied to other extracranial organs, nor can they simultaneously measure the critical closure pressure (CCP) of other organs, thus limiting the development of clinical hemodynamic therapy. Summary of the Invention

[0006] Based on this, and in response to the aforementioned technical problems, a device, equipment, and operating method for simultaneous monitoring of critical closure pressure in multiple organ arteries are provided to address the technical issue that existing methods for measuring critical closure pressure require prior assumptions of an intracranial pressure of 12 mmHg, which may lead to biased results and mislead clinical treatment.

[0007] To achieve the above objectives, this application provides the following technical solution:

[0008] In a first aspect, a multi-organ arterial critical closure pressure synchronous monitoring device includes:

[0009] The waveform acquisition module is used to acquire the radial artery pressure waveform and the arterial blood flow velocity waveforms of multiple organs simultaneously.

[0010] The data cleaning module is used to clean the radial artery pressure waveform and the arterial blood flow velocity waveforms of multiple organs.

[0011] The feature recognition module is used to perform feature recognition on the radial artery pressure waveform and the arterial blood flow velocity waveform of each organ, and to determine the rising and falling branches of the radial artery pressure waveform and the arterial blood flow velocity waveform of each organ.

[0012] The linear regression calculation module is used to perform linear regression calculations on the rising or falling limb of the arterial blood flow velocity waveform of each organ and the rising or falling limb of the radial artery pressure waveform. The blood pressure value when the corresponding regression line velocity of each organ is zero is the real-time critical closure pressure of that organ.

[0013] Optionally, radial artery pressure waveforms can be acquired using an invasive pressure sensor, and arterial blood flow velocity waveforms of multiple organs can be acquired simultaneously using multiple ultrasound Doppler probes.

[0014] Optionally, the findpeakm function in the MATLAB software toolbox can be used to perform feature recognition on the radial artery pressure waveform and the arterial blood flow velocity waveform of each organ.

[0015] Optionally, the feature identification of the radial artery pressure waveform and the arterial blood flow velocity waveform of each organ includes continuously marking the rising and falling branches of the radial artery pressure waveform and the arterial blood flow velocity waveform of each organ at a frequency of 200 Hz.

[0016] Optionally, the device further includes:

[0017] The waveform synchronization module is used to synchronize the radial artery pressure waveform and the arterial blood flow velocity waveform of each organ, respectively.

[0018] Optionally, the device further includes:

[0019] The diastolic time constant calculation module is used to calculate the arterial diastolic time constant based on the Windkessel model and using the formula τ=TRP*AC;

[0020] TRP is the total peripheral resistance of the body. TRP is expressed by the formula... Calculate, where MAP is the mean arterial pressure, RAP is the right atrial pressure, and C0 is the cardiac output;

[0021] AC stands for total arterial compliance, and AC is expressed by the formula... The calculation is performed, where SV is the stroke volume and K is the ratio between the total area under arterial pressure and the diastolic area, i.e., the area between the dicrotic notch and the end-diastolic area. P is the arterial pressure at the time of dicrotic notch occurrence. d This represents the arterial pressure at the end of diastole.

[0022] In a second aspect, a multi-organ arterial critical closure pressure synchronous monitoring device includes the multi-organ arterial critical closure pressure synchronous monitoring device described in any one of the first aspects, and an acquisition device for synchronously acquiring radial artery pressure waveforms and arterial blood flow velocity waveforms of multiple organs.

[0023] Thirdly, a method for operating a multi-organ arterial critical closure pressure synchronous monitoring device, characterized in that it includes:

[0024] Acquire the radial artery pressure waveform and arterial blood flow velocity waveforms of multiple organs simultaneously;

[0025] Data cleaning was performed on the radial artery pressure waveform and the arterial blood flow velocity waveforms of multiple organs;

[0026] Feature identification is performed on the radial artery pressure waveform and the arterial blood flow velocity waveform of each organ to determine the rising and falling branches of the radial artery pressure waveform and the arterial blood flow velocity waveform of each organ;

[0027] Linear regression calculations are performed on the rising or falling limb of the arterial blood flow velocity waveform of each organ and the rising or falling limb of the radial artery pressure waveform. The blood pressure value at which the corresponding regression line velocity of each organ is zero is the real-time critical closure pressure of that organ.

[0028] Fourthly, a computer device includes a memory and a processor, the memory storing a computer program, characterized in that the processor executes the computer program to implement the steps of the method described in the third aspect.

[0029] Fifthly, a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the method described in the third aspect.

[0030] The present invention has at least the following beneficial effects:

[0031] In the multi-organ arterial critical closure pressure synchronous monitoring device provided in this embodiment of the invention, by acquiring the arterial blood flow velocity waveform and radial artery pressure waveform of multiple organs simultaneously, and then separating the pressure waveform and the flow velocity waveform of each organ during the systolic phase (corresponding to the ascending branch) and diastolic phase (corresponding to the descending branch), the pressure and blood flow velocity of the multiple waveforms during the systolic or diastolic phases are regressed. The blood pressure value at the point where the flow velocity of the regression line is zero is the critical closure pressure of that organ at that time. Using the multi-organ arterial critical closure pressure synchronous monitoring device provided in this embodiment of the invention, the critical closure pressure of the organ can be obtained without presetting the organ perfusion pressure value or presetting the intracranial pressure to 12 mmHg, which largely avoids human error. Using the multi-organ arterial critical closure pressure synchronous monitoring device provided in this embodiment of the invention, the arterial critical closure pressure of multiple organs can be obtained simultaneously, realizing personalized optimal blood pressure titration based on multiple target organs, providing very important data reference for the determination and optimization of the optimal organ perfusion pressure in the subsequent hemodynamic treatment of shock patients. Attached Figure Description

[0032] Figure 1 This is a block diagram of the modular architecture of a multi-organ arterial critical closure pressure synchronous monitoring device according to an embodiment of the present invention;

[0033] Figure 2 A flowchart illustrating the operation method of a multi-organ arterial critical closure pressure synchronous monitoring device according to an embodiment of the present invention;

[0034] Figure 3 This is another schematic flowchart illustrating the operation method of a multi-organ arterial critical closure pressure synchronous monitoring device according to an embodiment of the present invention;

[0035] Figure 4 This is an internal structural diagram of a computer device provided in one embodiment of the present invention. Detailed Implementation

[0036] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0037] In one embodiment, such as Figure 1 As shown, a multi-organ arterial critical closure pressure synchronous monitoring device is provided, including the following program modules:

[0038] The waveform acquisition module 101 is used to acquire the radial artery pressure waveform and the arterial blood flow velocity waveform of multiple organs simultaneously.

[0039] Specifically, radial artery pressure waveforms are acquired using an invasive pressure sensor, and arterial blood flow velocity waveforms of multiple organs are acquired simultaneously using multiple ultrasound Doppler probes.

[0040] The data cleaning module 102 is used to clean the radial artery pressure waveform and the arterial blood flow velocity waveform of multiple organs.

[0041] Specifically, relatively stable basic data waveforms are obtained through bandpass filtering and outlier filtering.

[0042] The feature recognition module 103 is used to perform feature recognition on the radial artery pressure waveform and the arterial blood flow velocity waveform of each organ, and to determine the rising and falling branches of the radial artery pressure waveform and the arterial blood flow velocity waveform of each organ. The rising and falling branches correspond to the systolic and diastolic phases, respectively.

[0043] Furthermore, specifically, the findpeakm function in the MATLAB software toolbox is used to perform feature recognition on the radial artery pressure waveform and the arterial blood flow velocity waveform of each organ.

[0044] In other words, feature recognition is performed using the peak and valley detection function findpeakm in the MATLAB toolbox: [K,V]=findpeakm(x,m,w). Here, the input variable x is the sequence being tested; m is the method, where K is used to find peaks through quadratic curve interpolation, and V is used to find valleys; w is the number of sample points required for the minimum interval between two peaks when searching for peaks.

[0045] Furthermore, feature identification is performed on the radial artery pressure waveform and the arterial blood flow velocity waveform of each organ, including continuously marking the rising and falling branches of the radial artery pressure waveform and the arterial blood flow velocity waveform of each organ at a frequency of 200 Hz.

[0046] The linear regression calculation module 104 is used to perform linear regression calculations on the rising or falling branch of the arterial blood flow velocity waveform of each organ and the rising or falling branch of the radial artery pressure waveform. The blood pressure value when the corresponding regression line velocity of each organ is zero is the real-time critical closure pressure of that organ.

[0047] In other words, by performing regression analysis on the pressure and blood flow velocity during the systolic and diastolic phases of multiple waveforms, the blood pressure value at which the regression line velocity is zero is the critical closure pressure of that organ at that time.

[0048] Furthermore, the device also includes:

[0049] The waveform synchronization module is used to synchronize the radial artery pressure waveform and the arterial blood flow velocity waveform of each organ, respectively.

[0050] In other words, before performing linear regression calculations, based on the peak values ​​of the waveforms, a software algorithm synchronizes blood flow in multiple sites at the millisecond level. Specifically, Python is used to process each waveform to determine the starting point, peak, and the cutoff point of the descending branch. By synchronizing the peaks of the same beat, the data points of the rising and falling branches of the pressure and flow velocity waveforms of each organ are then matched one by one to achieve regression analysis.

[0051] Furthermore, the device also includes:

[0052] The diastolic time constant calculation module is used to calculate the arterial diastolic time constant based on the Windkessel model using the formula τ=TPR*AC;

[0053] TPR is the total peripheral resistance of the body, and TRP is expressed by the formula... The calculation is performed, where MAP is the mean arterial pressure, RAP is the right atrial pressure, and C0 is the cardiac output; it is assumed that the right atrial pressure (RAP) is zero, which is much lower than the arterial pressure, and therefore can be ignored.

[0054] AC stands for total arterial compliance, and AC is expressed by the formula... The calculation is performed, where SV is the stroke volume and K is the ratio between the total area under arterial pressure and the diastolic area, i.e., the area between the dicrotic notch and the end-diastolic area. P is the arterial pressure at the time of dicrotic notch occurrence. d This represents the arterial pressure at the end of diastole.

[0055] In other words, the diastolic time constant can also be calculated based on blood pressure and the slope of the descending blood flow branch.

[0056] In the multi-organ arterial critical closure pressure synchronous monitoring device provided in this embodiment of the invention, the arterial blood flow velocity waveform and radial artery pressure waveform of multiple organs are acquired synchronously. Then, the pressure waveform and the flow velocity waveform of each organ are separated during the systolic and diastolic phases. The pressure and blood flow velocity regressions of the multiple waveforms during the systolic and diastolic phases are performed respectively. The blood pressure value at the point where the regression line velocity is zero is the critical closure pressure of that organ at that time. Using the multi-organ arterial critical closure pressure synchronous monitoring device provided in this embodiment of the invention, the critical closure pressure of an organ can be obtained without pre-setting organ perfusion pressure values ​​or pre-setting intracranial pressure to 12 mmHg, largely avoiding human error.

[0057] Furthermore, traditional methods can only be used to measure the critical closure pressure of cerebral blood vessels and cannot measure the critical closure pressure (CCP) of other organs. However, the multi-organ arterial critical closure pressure synchronous monitoring device provided in this embodiment of the invention can simultaneously obtain the arterial critical closure pressure of multiple organs, realizing personalized optimal blood pressure titration based on multiple target organs. This provides a very important data reference for the determination and optimization of the optimal organ perfusion pressure in the subsequent hemodynamic treatment of shock patients.

[0058] The multi-organ arterial critical closure pressure synchronous monitoring device provided in this invention provides an achievable means for continuous dynamic monitoring of multi-organ arterial critical closure pressure, enabling the assessment of the correlation between clinical autonomic nervous system regulation mechanisms and peripheral blood vessels and central circulation, and bringing innovation to hemodynamic research and clinical practice.

[0059] The modules in the multi-organ arterial critical closure pressure synchronous monitoring device provided in this invention can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in a computer device in hardware form, or stored in the memory of a computer device in software form, so that the processor can call and execute the operations corresponding to each module.

[0060] In one embodiment, a multi-organ arterial critical closure pressure synchronous monitoring device is provided, including the multi-organ arterial critical closure pressure synchronous monitoring device provided in the above embodiment, and a data acquisition device for synchronously acquiring radial artery pressure waveforms and arterial blood flow velocity waveforms of multiple organs.

[0061] The acquisition device may specifically include an invasive pressure sensor and multiple ultrasound Doppler probes.

[0062] In one embodiment, such as Figure 2 As shown, a method for operating a multi-organ arterial critical closure pressure synchronous monitoring device is provided, including the following steps:

[0063] S201, acquire the radial artery pressure waveform and arterial blood flow velocity waveforms of multiple organs simultaneously.

[0064] Specifically, radial artery pressure waveforms are acquired using an invasive pressure sensor, and arterial blood flow velocity waveforms of multiple organs are acquired simultaneously using multiple ultrasound Doppler probes.

[0065] S202 performs data cleaning on radial artery pressure waveforms and arterial blood flow velocity waveforms from multiple organs.

[0066] Specifically, relatively stable basic data waveforms are obtained through bandpass filtering and outlier filtering.

[0067] S203 performs feature recognition on the radial artery pressure waveform and the arterial blood flow velocity waveform of each organ, and determines the ascending and descending branches of the radial artery pressure waveform and the arterial blood flow velocity waveform of each organ. The ascending and descending branches correspond to the systolic and diastolic phases, respectively.

[0068] Furthermore, specifically, the findpeakm function in the MATLAB software toolbox is used to perform feature recognition on the radial artery pressure waveform and the arterial blood flow velocity waveform of each organ.

[0069] In other words, feature recognition is performed using the peak and valley detection function findpeakm in the MATLAB toolbox: [K,V]=findpeakm(x,m,w). Here, the input variable x is the sequence being tested; m is the method, where K is used to find peaks through quadratic curve interpolation, and V is used to find valleys; w is the number of sample points required for the minimum interval between two peaks when searching for peaks.

[0070] Furthermore, feature identification is performed on the radial artery pressure waveform and the arterial blood flow velocity waveform of each organ, including continuously marking the rising and falling branches of the radial artery pressure waveform and the arterial blood flow velocity waveform of each organ at a frequency of 200 Hz.

[0071] S204, perform linear regression calculations on the rising or falling limbs of the arterial blood flow velocity waveform of each organ and the rising or falling limbs of the radial artery pressure waveform. The blood pressure value when the corresponding regression line velocity of each organ is zero is the real-time critical closure pressure of that organ.

[0072] In other words, by performing regression analysis on the pressure and blood flow velocity during the systolic and diastolic phases of multiple waveforms, the blood pressure value at which the regression line velocity is zero is the critical closure pressure of that organ at that time.

[0073] Furthermore, the method also includes:

[0074] The radial artery pressure waveform and the arterial blood flow velocity waveform of each organ were synchronized.

[0075] In other words, before performing linear regression calculations, based on the peak values ​​of the waveforms, a software algorithm synchronizes blood flow in multiple sites at the millisecond level. Specifically, Python is used to process each waveform to determine the starting point, peak, and the cutoff point of the descending branch. By synchronizing the peaks of the same beat, the data points of the rising and falling branches of the pressure and flow velocity waveforms of each organ are then matched one by one to achieve regression analysis.

[0076] Furthermore, the method also includes:

[0077] Based on the Windkessel model, the arterial diastolic time constant is calculated using the formula τ = TPR * AC.

[0078] TPR is the total peripheral resistance of the body. TPR is expressed by the formula... Calculate, where MAP is the mean arterial pressure, RAP is the right atrial pressure, and C0 is the cardiac output;

[0079] AC stands for total arterial compliance, and AC is expressed by the formula... The calculation is performed, where SV is the stroke volume and K is the ratio between the total area under arterial pressure and the diastolic area, i.e., the area between the dicrotic notch and the end-diastolic area. P is the arterial pressure at the time of dicrotic notch occurrence. d This represents the arterial pressure at the end of diastole.

[0080] In other words, the diastolic time constant can also be calculated based on blood pressure and the slope of the descending blood flow branch.

[0081] Another flowchart illustrating the operating method provided in this embodiment of the invention can be found here. Figure 3 .

[0082] It should be understood that, although Figure 2-3 The steps in the flowchart are shown sequentially as indicated by the arrows, but these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order in which these steps are executed, and they can be performed in other orders. Figure 2-3 At least some of the steps in the process may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same time, but may be executed at different times. The execution order of these steps or stages is not necessarily sequential, but may be executed in turn or alternately with other steps or at least some of the steps or stages in other steps.

[0083] In one embodiment, a computer device is provided, which may be a terminal, and its internal structure diagram may be as follows: Figure 4As shown, the computer device includes a processor, memory, communication interface, display screen, and input devices connected via a system bus. The processor provides computing and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The communication interface is used for wired or wireless communication with external terminals; wireless communication can be achieved through Wi-Fi, carrier networks, NFC (Near Field Communication), or other technologies. When the computer program is executed by the processor, it implements a method for operating a multi-organ arterial critical closure pressure synchronous monitoring device. The display screen can be an LCD screen or an e-ink screen. The input devices can be a touch layer covering the display screen, buttons, a trackball, or a touchpad on the computer device casing, or an external keyboard, touchpad, or mouse.

[0084] Those skilled in the art will understand that Figure 4 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0085] In one embodiment, a computer device is provided, including a memory and a processor, wherein the memory stores a computer program relating to all or part of the processes in the methods of the above embodiments.

[0086] In one embodiment, a computer-readable storage medium is provided having a computer program stored thereon relating to all or part of the processes in the methods of the above embodiments.

[0087] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the methods described above. Any references to memory, storage, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, or optical storage, etc. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM), etc.

[0088] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0089] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the invention patent. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this patent application should be determined by the appended claims.

Claims

1. A multi-organ arterial critical closing pressure synchronous monitoring device, characterized in that, include: The waveform acquisition module is used to acquire the radial artery pressure waveform and the arterial blood flow velocity waveforms of multiple organs simultaneously. The data cleaning module is used to clean the radial artery pressure waveform and the arterial blood flow velocity waveforms of multiple organs. The feature recognition module is used to perform feature recognition on the radial artery pressure waveform and the arterial blood flow velocity waveform of each organ, and to determine the rising and falling branches of the radial artery pressure waveform and the arterial blood flow velocity waveform of each organ. The waveform synchronization module is used to synchronize the radial artery pressure waveform and the arterial blood flow velocity waveform of each organ. Specifically, before performing linear regression calculation, based on the waveform peak value, a software algorithm synchronizes blood flow at multiple sites at millisecond-level clock speeds. Specifically, Python is used to process each waveform to determine the starting point, peak, and descent cutoff point. By synchronizing the apex of the same beat, the data points of the rising and falling branches of the pressure and arterial blood flow velocity waveforms of each organ are then matched one-to-one to achieve regression analysis. The linear regression calculation module is used to perform linear regression calculations on the rising or falling branch of the arterial blood flow velocity waveform of each organ and the rising or falling branch of the radial artery pressure waveform. The blood pressure value when the corresponding regression line arterial blood flow velocity of each organ is zero is the real-time critical closure pressure of that organ.

2. The multi-organ arterial critical closing pressure synchronous monitoring device according to claim 1, characterized in that, Radial artery pressure waveforms were acquired using an invasive pressure sensor, and arterial blood flow velocity waveforms from multiple organs were simultaneously acquired using multiple ultrasound Doppler probes.

3. The multi-organ critical closing pressure synchronous monitoring device according to claim 1, characterized in that, The findpeaks function in the MATLAB software toolbox was used to identify features of the radial artery pressure waveform and the arterial blood flow velocity waveform of each organ.

4. The multi-organ critical closing pressure synchronous monitoring device according to claim 1, characterized in that, The feature identification of the radial artery pressure waveform and the arterial blood flow velocity waveform of each organ includes continuously marking the rising and falling branches of the radial artery pressure waveform and the arterial blood flow velocity waveform of each organ at a frequency of 200 Hz.

5. The multi-organ arterial critical closure pressure synchronous monitoring device according to claim 1, characterized in that, The device further includes: The diastolic time constant calculation module is used to calculate the diastolic time constant based on the Windkessel model using the formula. Calculate the arterial diastolic time constant, where, This is the arterial diastolic time constant; TPR is the total peripheral resistance of the body. TPR is expressed by the formula... Calculate, where MAP is the mean arterial pressure, RAP is the right atrial pressure, and CO is the cardiac output; AC stands for total arterial compliance, and AC is expressed by the formula... The calculation is performed, where SV is the stroke volume and K is the ratio between the total area under arterial pressure and the diastolic area. , This refers to the arterial pressure at the time of dicrotic notch occurrence. Arterial pressure at the end of diastole For the area during the shrinkage period, This refers to the diastolic area.

6. A multi-organ arterial critical closure pressure synchronous monitoring device, characterized in that, The invention includes the multi-organ arterial critical closure pressure synchronous monitoring device according to any one of claims 1 to 5, and the acquisition device for synchronously acquiring radial artery pressure waveforms and arterial blood flow velocity waveforms of multiple organs.

7. A method for operating a multi-organ arterial critical closure pressure synchronous monitoring device, characterized in that, include: Acquire the radial artery pressure waveform and arterial blood flow velocity waveforms of multiple organs simultaneously; Data cleaning was performed on the radial artery pressure waveform and the arterial blood flow velocity waveforms of multiple organs; Feature identification is performed on the radial artery pressure waveform and the arterial blood flow velocity waveform of each organ to determine the rising and falling branches of the radial artery pressure waveform and the arterial blood flow velocity waveform of each organ; The radial artery pressure waveform and the arterial blood flow velocity waveform of each organ are synchronized. Specifically, before performing linear regression calculation, based on the waveform peak value, the blood flow of multiple sites is synchronized at the millisecond level using a software algorithm. Specifically, Python is used to process each waveform to determine the starting point, peak, and descent branch cutoff point. By synchronizing the apex of the same beat, the data points of the rising and falling branches of the pressure and arterial blood flow velocity waveforms of each organ are then matched one by one to achieve regression analysis. Linear regression calculations are performed on the rising or falling limb of the arterial blood flow velocity waveform of each organ and the rising or falling limb of the radial artery pressure waveform. The blood pressure value at which the corresponding regression line arterial blood flow velocity of each organ is zero is the real-time critical closure pressure of that organ.

8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method described in claim 7.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the steps of the method described in claim 7.

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