Control system and method for personalized treatment of left ventricle auxiliary device

Abstract

The invention provides a control system and method for personalized treatment of a left ventricular assist device, and relates to the technical field of artificial hearts.The method comprises the steps that for each cardiac cycle, after a Starling-like regulator receives a left atrium pressure signal fed back by a physiological feedback module, an expected cardiac index is output according to the body surface area of a patient; the pump flow quantitative feedback module calculates the pump flow in real time according to the rotating speed and the current of the left ventricular assist device, and outputs a feedback heart index in combination with the body surface area of the patient; the deviation between the expected heart index and the feedback heart index is calculated, the deviation is input into a controller, and the controller determines the output current increment according to the deviation condition; and the process is repeated until the control system is stable. Ventricular pressure monitoring is performed through the physiological feedback module and the cardiovascular coupling module, personalized physiological feature analysis is performed in combination with the body surface area of a patient, and pump speed parameters can be automatically optimized according to the real-time physiological state of the patient.

Description

Technical Field

[0001] The present application relates to the field of artificial heart technology, and more specifically, to a control system and method for personalized treatment of a left ventricular assist device. Background Art

[0002] The Left Ventricular Assist Device (LVAD) is used to pump blood from the left ventricle into the aorta, thereby reducing the burden on the left ventricle and providing stable blood circulation. It plays an important role in the treatment of end-stage heart failure. The development of LVAD has undergone three important technological innovations. The first generation of LVAD uses pulsatile blood flow technology, and its design simulates the beating pattern of the natural heart, but its size is large due to its complex mechanical structure. The second generation of LVAD innovatively uses mechanical bearing technology, which not only significantly reduces the size of the device, but also greatly improves the mechanical durability, but there are problems of mechanical wear and heat. The latest generation of LVAD uses suspension technology, which has made breakthrough progress in reducing the risk of thrombosis and improving blood compatibility by completely eliminating mechanical contact parts, while further reducing mechanical wear. These technological advances have enabled LVAD to be continuously optimized in terms of miniaturization, reliability and biocompatibility, providing a safer and more effective treatment option for patients with end-stage heart failure. Although the design of LVAD has made great progress, the existing LVAD control system mostly adopts fixed speed or simple feedback adjustment based on a single parameter, which has significant limitations. The typical LVAD control schemes in the prior art are: (1) The Chinese invention patent with publication number CN109793954A discloses an indifferent adaptive physiological control method based on a left ventricular assist device (LVAD). First, the preload from the left ventricle is measured and used as the input value of the Frank-Starling like control system to generate the reference value of the average pump flow and the reference value of the pulsation value of the pump flow required by the patient. In the signal processing module, the Savitzky-Golay (SG) filter, the extended Kalman filter and the low-pass filter are used to remove noise from the extracted pump speed signal, and the required average pump flow and the pulsation value of the flow are estimated (Qplus). Finally, the PI controller is input for processing, and the output current signal directly controls the LVAD to achieve the desired pump speed. This scheme lacks the ability to adapt to individual differences of patients (such as physiological structure, pathological state) and dynamic physiological state (such as exercise, sleep), and is prone to complications such as ventricular insufficiency or insufficient perfusion.

[0003] (2)The Chinese invention patent with the publication number CN115016256A discloses an MPC control method based on the physiological adaptation of a left ventricular assist device. By obtaining the left ventricular pressure measurement value LVP and using it as the input value of the aortic pressure neural network model, the aortic pressure reference value AOPref required by the patient is obtained through the aortic pressure neural network model; the LVAD motor speed Ps is obtained, the pump flow Qp is estimated through denoising processing by a low-pass filter and the power pump flow relationship, and the safe pump flow Qs is obtained after suction and reflux monitoring; the patient's aortic pressure AOP is obtained, and AOPref is used as the reference value, and LVP, AOP, and Qs are used as system states to be processed by the MPC controller, and the output current signal I controls the LVAD to achieve the rotation speed that meets the patient's physiology. This control strategy is difficult to quickly respond to sudden changes in physiological parameters and lacks an intelligent decision-making mechanism for multi-parameter fusion.

[0004] In view of these problems, there is an urgent need to develop a control system that can integrate multi-dimensional physiological data in real time, dynamically optimize the pump speed using intelligent algorithms, and support personalized treatment of left ventricular assist devices to improve clinical safety and treatment adaptability. Summary of the Invention

[0005] To solve the above problems, the technical solution adopted in this application is a control method for personalized treatment of a left ventricular assist device: for each cardiac cycle, after the Starling-like regulator receives the left atrial pressure signal fed back by the physiological feedback module, it outputs the expected cardiac index according to the patient's body surface area; the pump flow quantization feedback module calculates the pump flow in real time based on the rotation speed and current of the left ventricular assist device, and combines the patient's body surface area to output the feedback cardiac index; the deviation between the expected cardiac index and the feedback cardiac index is calculated, and the deviation is input into the controller, and the controller decides the output current increment according to the situation of the deviation. In each subsequent cardiac cycle, the above process is repeated until the control system is stable.

[0006] Optionally, the expected cardiac index is calculated according to the following formula: ; ; In the formula, is the expected cardiac index, is the expected cardiac output, BSA is the body surface area, is the height, is the weight.

[0007] Optionally, the expected cardiac output is calculated according to the following formula: ; Wherein, is the desired cardiac output, is the left atrial pressure, is a scaling factor that simulates the sensitivity of the desired pump flow to the left atrial pressure due to changes in myocardial contractility.

[0008] Optionally, the scaling factor is calculated according to the following formula: ; Wherein, represents the myocardial contractility coefficient, represents the ventricular systolic time coefficient, represents the baseline time reference, represents the heart rate.

[0009] Optionally, the ventricular systolic time coefficient and the baseline time reference are related to the cardiac cycle , the left ventricular diastolic time and the left ventricular systolic time as follows: ; ; = - .

[0010] Optionally, the controller is designed based on a fuzzy control algorithm. The input of the controller is the deviation between the desired cardiac index and the feedback cardiac index and the rate of change of the deviation, and the output of the controller is the current increment of the rotary pump of the left ventricular assist device.

[0011] Optionally, the calculation of the current increment includes: S1: Fuzzification interface; The fuzzy subsets of the deviation are divided into: Deviation = {Negative large, Negative medium, Negative small, Negative zero, Positive zero, Positive small, Positive medium, Positive large} = {NB, NM, NS, NZ, PZ, PS, PM, PB}; The fuzzy subsets of the rate of change of the deviation are divided into: Rate of change of deviation = {Negative large, Negative medium, Negative small, Negative zero, Positive zero, Positive small, Positive medium, Positive large} = {NB, NM, NS, NZ, PZ, PS, PM, PB}; The fuzzy subsets of the phase current are divided into: Phase current = {Negative large, Negative medium, Negative small, Negative zero, Positive zero, Positive small, Positive medium, Positive large} = {NB, NM, NS, NZ, PZ, PS, PM, PB}; The universes of discourse of the deviation and the deviation change rate are {-6, -5, -4, -3, -2, -1, 0, 1, 2, 3, 4, 5, 6}, and the membership functions are all triangular membership functions; S2: Formulate a fuzzy rule table for the current increment based on the deviation and the deviation change rate; S3: Defuzzification, calculate the quantization value of the current increment using the centroid method, according to the following formula: ; In the formula, represents the current increment after defuzzification, represents the phase current fuzzy quantity corresponding to the current increment, represents the membership value corresponding to the fuzzy quantity, is the total number of discretized output quantities.

[0012] Optionally, the calculation of the feedback cardiac index includes: Pump flow estimation: The expression for pump flow estimation is as follows: ; In the formula, is the estimated pump flow, is the rotor inertia, is the rotational speed, is the back electromotive force constant, is the current, is the damping coefficient, , are the correlation coefficients; Pump flow feature extraction: Pump flow feature extraction refers to extracting the average pump flow from the set of estimated pump flow data. The formula for the average pump flow is as follows: ; In the formula, is the average pump flow, is the total number of samples within a cardiac cycle, and j is the index variable used to represent the sample point number within a cardiac cycle; Feedback cardiac index: The formula for the feedback cardiac index is as follows: ; In the formula, is the feedback cardiac index.

[0013] Optionally, the left atrial pressure signal feedback by the physiological feedback module is the average left atrial pressure extracted by the physiological feedback module from the cardiovascular coupling system, and the calculation is carried out according to the following formula: ; In the formula, is the average left atrial pressure, where \(N\) is the total number of samples within one cardiac cycle, and \(j\) is an index variable used to represent the sample point number within one cardiac cycle.

[0014] The present application also provides a control system for personalized treatment of a left ventricular assist device, including a left ventricular assist device, a cardiovascular coupling system, and a physiological feedback module, which is applicable to the control method for personalized treatment of a left ventricular assist device as described in any one of the foregoing, including: Starling-like regulator: configured to receive the left atrial pressure signal fed back by the physiological feedback module and output a desired cardiac index based on the patient's body surface area; Pump flow quantification feedback module: configured to calculate the pump flow in real time according to the rotational speed and current of the rotary pump of the left ventricular assist device, and output the feedback cardiac index in combination with the patient's body surface area; Controller: configured to determine the output current increment according to the input deviation condition; Physiological feedback module: configured to receive the left atrial pressure signal of the cardiovascular coupling system and feed it back to the Starling-like regulator.

[0015] The beneficial effects of the control system and method for personalized treatment of a left ventricular assist device provided by the present application are as follows: By means of the left atrial pressure signal fed back by the physiological feedback module, a desired cardiac index is output based on the patient's body surface area. The pump flow is calculated in real time according to the rotational speed and current of the rotary pump of the left ventricular assist device, and the feedback cardiac index is output in combination with the patient's body surface area. The output current increment is determined according to the input deviation condition. Through the physiological feedback module and the cardiovascular coupling module, the atrial pressure is monitored, and the patient's personalized physiological characteristics are analyzed in combination with the patient's body surface area, realizing precise and adaptive circulatory support. This innovative design enables the left ventricular assist device to automatically optimize the pump speed parameters according to the patient's real-time physiological state (such as the transition between exercise / rest and changes in fluid balance), avoiding excessive ventricular unloading while ensuring sufficient cardiac output, providing personalized blood flow support that better meets physiological needs, and significantly reducing the risks of common complications such as right heart failure, thromboembolism, and gastrointestinal bleeding in the treatment of traditional left ventricular assist devices, providing a safer and more effective mechanical circulatory support solution for patients with advanced heart failure. Description of the Drawings

[0016] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the following will briefly introduce the drawings required for use in the embodiments or the description of the prior art.

[0017] Figure 1 It is a block diagram of the control system for personalized treatment of a left ventricular assist device provided by the embodiment of the present application; Figure 2It is the operation flowchart of the control system provided by the embodiments of the present application; Figure 3 It is the current change diagram of different patients during the transition from rest to exercise provided by the embodiments of the present application; Figure 4 It is the pump speed change diagram of different patients during the transition from rest to exercise provided by the embodiments of the present application; Figure 5 It is the cardiac output change diagram of different patients during the transition from rest to exercise provided by the embodiments of the present application. Specific Embodiments

[0018] In order to make the technical problems, technical solutions and beneficial effects to be solved by the present application clearer, the present application will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0019] Embodiment 1 As Figure 1 shown, the present application provides a control system for personalized treatment of a left ventricular assist device, including a left ventricular assist device, a cardiovascular coupling system and a physiological feedback module, including: Starling-like regulator: used to receive the left atrial pressure signal fed back by the physiological feedback module, and output the desired cardiac index based on the patient's body surface area; Pump flow quantization feedback module: used to calculate the pump flow in real time according to the rotational pump speed and current of the left ventricular assist device, and output the feedback cardiac index in combination with the patient's body surface area; Controller: used to determine the output current increment according to the situation of the input deviation; Physiological feedback module: used to receive the left atrial pressure signal of the cardiovascular coupling system and feed it back to the Starling-like regulator.

[0020] The Starling-like regulator mimics the inherent Starling mechanism of the heart, and the construction process includes the following steps: Step 1: Design a Starling-like controller to describe the relationship between the desired cardiac output of the system and the left atrial pressure.

[0021] Step 2: Quantify the desired cardiac output in combination with individual characteristic parameters as an index for individualized evaluation and clinical application.

[0022] The relationship expression between the desired cardiac output and the left atrial pressure is as follows:

[0023] In the formula, is the desired cardiac output, is the left atrial pressure, is a scaling factor that simulates the change in myocardial contractility and the sensitivity of the desired pump flow to the left atrial pressure.

[0024] The scaling factor is calculated according to the following formula: ; wherein, represents the myocardial contractility coefficient, represents the ventricular systolic time coefficient, represents the baseline time reference, represents the heart rate.

[0025] Ventricular systolic time coefficient and baseline time reference are related to the cardiac cycle and the left ventricular diastolic time and the left ventricular systolic time as follows: ; ; = - ; In this embodiment, the ventricular systolic time coefficient and the baseline time reference and the myocardial contractility coefficient are determined according to the following conditions: (1) At rest, the ratio of ventricular systolic to diastolic time is ; (2) For healthy adults, is 75 bpm, is 1, corresponding to a cardiac output of 5 L / min; (3) According to the necessary and sufficient conditions for the extreme value, when , reaches the maximum value. For normal people, when the heart rate is 180 bpm, begins to decline, that is, .

[0026] Based on the above conditions, , , .

[0027] Myocardial contractility is related to the activity intensity, and the change in heart rate directly reflects the activity level. Therefore, a functional relationship between the scaling factor and the heart rate is established as follows:

[0028] The above shows the calculations and values under standard conditions. For each individual, the following adjustments are made separately: For condition (1), monitor the heart rate and collect the ratio of ventricular systolic to diastolic time; For condition (2), based on the corresponding age group and gender, determine the reference value of the heart rate at rest and the corresponding cardiac output, and then formulate the reference value of the scaling factor; For condition (3), using the maximum value of its heart rate as the basis for starting to decline, and then determine the value of.

[0029] According to the above method, the present application provides a calculation method for the scaling factor, and the calculation of this scaling factor does not require invasive monitoring, providing convenience for personalized treatment.

[0030] The individual characteristic parameters are body surface area, height, and weight, and the index for individualized assessment and clinical application is cardiac index.

[0031] The relationship between body surface area, height, and weight is as follows: ; In the formula, BSA is the body surface area (cubic meters), is the height (centimeters), is the weight (kilograms).

[0032] The formula for calculating the expected value of cardiac index is as follows: ; In the formula, is the expected cardiac index.

[0033] The controller is designed based on an intelligent control algorithm. The input of the controller is the deviation between the expected cardiac index and the feedback cardiac index and the rate of change of the deviation. The output of the controller is the current increment of the left ventricular assist device rotary pump, as Figure 1 shown. The expected cardiac index and the feedback cardiac index are first input into the discriminator. After the calculation of the discriminator, the deviation between the expected cardiac index and the feedback cardiac index and the rate of change of the deviation are obtained.

[0034] The controller is a fuzzy controller.

[0035] The design steps of the fuzzy controller are as follows: Step 1: Fuzzification interface.

[0036] The fuzzy subsets of the deviation are divided into: Deviation = {Negative Large, Negative Medium, Negative Small, Negative Zero, Positive Zero, Positive Small, Positive Medium, Positive Large} = {NB, NM, NS, NZ, PZ, PS, PM, PB} The fuzzy subsets of the deviation change rate are divided as follows: Deviation change rate = {Negative Large, Negative Medium, Negative Small, Negative Zero, Positive Zero, Positive Small, Positive Medium, Positive Large} = {NB, NM, NS, NZ, PZ, PS, PM, PB} The fuzzy subsets of the motor phase current increment are divided as follows: Phase current = {Negative Large, Negative Medium, Negative Small, Negative Zero, Positive Zero, Positive Small, Positive Medium, Positive Large} = {NB, NM, NS, NZ, PZ, PS, PM, PB} The universes of discourse of the deviation and the deviation change rate are {-6, -5, -4, -3, -2, -1, 0, 1, 2, 3, 4, 5, 6}, and the membership functions are all triangular membership functions.

[0037] Step 2: Design the fuzzy rule table.

[0038] The fuzzy rules are shown in Table 1.

[0039] Table 1 Fuzzy rule table

[0040] Step 3: Defuzzification.

[0041] The centroid method is used to calculate the quantization value of the current increment. The formula is as follows: ; In the formula, represents the current increment after defuzzification, represents the fuzzy quantity corresponding to the current increment, represents the membership degree value corresponding to the fuzzy quantity, is the total number of discretized output quantities.

[0042] The core component of the left ventricular assist device is the rotary pump.

[0043] The model of the rotary pump includes a mechanical dynamics model and a hydraulics model.

[0044] The expression of the mechanical dynamics model is as follows: ; In the formula, is the rotor inertia, is the rotational speed, is the back electromotive force constant, is the current, is the damping coefficient, , is the correlation coefficient, is the pump flow rate.

[0045] The expression of the hydraulic model is as follows: ; In the formula, is the pump differential pressure, , , are experimental constants.

[0046] The cardiovascular coupling system is a prior art, which is used to simulate the hemodynamic characteristics of the cardiovascular system during the operation of a left ventricular assist device, including a cardiovascular lumped parameter model and a baroreflex model.

[0047] As a reference, the doctoral dissertation of Shandong University, "Research on Pulsatile Variable Speed and Physiological Control of a Continuous Flow Left Ventricular Assist Device" ([1] Liu Hongtao. Research on Pulsatile Variable Speed and Physiological Control of a Continuous Flow Left Ventricular Assist Device [D]. Shandong University, 2021. DOI: 10.27272 / d.cnki.gshdu.2021.006094.), Chapter 2, Hemodynamic Model of the Cardiovascular Coupling System provides a detailed modeling method for the hemodynamic model of the cardiovascular coupling system.

[0048] The cardiovascular coupling system referred to in this application is used to provide simulation feedback in in vitro experiments.

[0049] The cardiovascular lumped parameter model is used to simulate the hemodynamics of the cardiovascular system, and divides the blood circulation system into four parts: the left heart, the right heart, the systemic circulation, and the pulmonary circulation.

[0050] The baroreflex model is used to simulate the neural regulation of aortic pressure and regulates the end-systolic elastance of the left ventricle, the end-systolic elastance of the right ventricle, the systemic vascular resistance, and the heart rate in the cardiovascular lumped parameter model.

[0051] The quantitative feedback of the pump flow rate includes pump flow rate estimation and pump flow rate feature extraction.

[0052] The expression of the pump flow rate estimation is as follows: ; In the formula, is the estimated pump flow rate.

[0053] Pump flow rate feature extraction refers to extracting the average pump flow rate from the set of estimated pump flow rate data.

[0054] The calculation formula of the average pump flow rate is as follows: ; In the formula, is the average pump flow rate, is the total amount of samples within one cardiac cycle.

[0055] The calculation formula for the feedback cardiac index is as follows: ; In the formula, is the feedback cardiac index.

[0056] The left atrial pressure signal feedback by the physiological feedback module is the average left atrial pressure extracted by the physiological feedback module from the cardiovascular coupling system, and is calculated according to the following formula: ; In the formula, is the average left atrial pressure, is the total amount of samples within one cardiac cycle, and j is an index variable used to represent the sampling point number within one cardiac cycle.

[0057] Embodiment 2: Figure 2 This is the execution method of the control system for personalized treatment of the left ventricular assist device provided by this application within one cardiac cycle. After receiving the patient's body surface area and the left atrial pressure signal feedback by the physiological feedback module, the Starling-like regulator outputs the desired cardiac index. At the same time, the feedback pump flow rate is quantified into the feedback cardiac index through the body surface area. Subsequently, the deviation between the desired cardiac index and the feedback cardiac index is calculated, and the deviation is input into the controller. The controller determines the positive or negative of the output current increment according to the input deviation. If the current increment is positive, the pump speed is high, otherwise the pump speed decreases. When the pump speed increases, the pump flow rate increases, otherwise the pump flow rate decreases. The increase or decrease of the pump flow rate will inevitably cause changes in the hemodynamics of the cardiovascular coupling system, especially the left atrial pressure. In the next cardiac cycle, the above process is repeated until the control system is stable.

[0058] Embodiment 3: Figures 3 - 5 It details the dynamic change laws of current, pump speed, and cardiac output during the transition from the resting state to the exercise state for patients with different body surface areas (1.64㎡ and 2.23㎡). In the initial resting stage (before the 20th second), the system automatically adjusts the support level according to the patient's body surface area: patients with a smaller body surface area (1.64㎡) obtain a basic cardiac output of 5 L / min, while patients with a larger body surface area (2.23㎡) obtain a support of 7 L / min. This difference in the initial setting reflects the accurate identification ability of the control system for the individual physiological needs of patients.

[0059] Starting from the 20th second, when the patient enters the exercise transition period, the control system demonstrates excellent dynamic regulation characteristics. Different from the fixed rotation speed mode of traditional mechanical pumps, this personalized control system adopts a progressive regulation strategy. First, it gently increases the drive current, and then drives the gradual increase of the pump speed, ultimately achieving an adaptive increase in cardiac output. This regulation process not only avoids violent fluctuations in hemodynamics but also ensures the smoothness of physiological transition, reflecting the optimized design of the control algorithm. After about 30 seconds of buffer adjustment, the system reaches a new exercise steady state. At this time, the cardiac output of the 1.64㎡ patient increases to 8 L / min, while that of the 2.23㎡ patient reaches 10.5 L / min. It is worth noting that although the body surface areas of the two patients differ by approximately 36%, the increase in cardiac output during exercise shows different characteristics (a 60% increase for the 1.64㎡ patient and a 50% increase for the 2.23㎡ patient). This indicates that the control system does not simply adjust proportionally but is optimized based on a more complex physiological demand model.

[0060] These results have important clinical significance. First, it verifies that the personalized control algorithm can achieve precise matching of the initial settings based on key parameters such as the patient's body surface area. Second, the smooth transition characteristics shown by the system during state conversion can effectively reduce the clinical risks brought by sudden changes in hemodynamics. In addition, the differential increase in cardiac output during exercise further confirms that the control system can dynamically adapt to the metabolic demand changes of different patients. These findings provide important references for the research and development of a new generation of intelligent ventricular assist devices, indicating that an adaptive regulation system based on physiological feedback can not only provide circulatory support that better meets individual needs but also maintain the best hemodynamic stability when the patient's daily activity state changes, thus providing a new technical solution for improving the quality of life and exercise tolerance of heart failure patients.

[0061] The above embodiments are only used to illustrate the technical solutions of the present application, not to limit them; although the present application has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements for some of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present application, and should all be included in the protection scope of the present application.

Claims

1. A control method for personalized treatment of a left ventricular assist device, characterized in that: For each cardiac cycle, after receiving the left atrial pressure signal fed back by the physiological feedback module, the Starling-like regulator outputs the desired cardiac index according to the patient's body surface area; The pump flow quantization feedback module calculates the pump flow in real time based on the rotational speed and current of the left ventricular assist device, combines the patient's body surface area, and outputs the feedback cardiac index; calculates the deviation between the desired cardiac index and the feedback cardiac index, and inputs the deviation into the controller. The controller determines the output current increment according to the situation of the deviation; In each subsequent cardiac cycle, the above process is repeated until the control system is stable.

2. The control method for personalized treatment of the left ventricular assist device according to claim 1, wherein: The desired cardiac index is calculated according to the following formula: ； ； Wherein, is the desired cardiac index, is the desired cardiac output, BSA is the body surface area, is the height, is the weight.

3. The control method for personalized treatment of the left ventricular assist device according to claim 2, characterized in that: The desired cardiac output is calculated according to the following formula: ； In the formula, is the desired cardiac output, is the left atrial pressure, is the scaling factor that simulates the change in myocardial contractility to alter the sensitivity of the desired pump flow to the left atrial pressure.

4. The control method for personalized treatment of the left ventricular assist device according to claim 3, wherein: The scaling factor is calculated according to the following formula: ； In the formula, represents the myocardial contractility coefficient, represents the ventricular systolic time coefficient, represents the baseline time reference, represents the heart rate.

5. The control method for personalized treatment of the left ventricular assist device according to claim 4, characterized in that: The ventricular systolic time coefficient and the baseline time reference are related to the cardiac cycle , the left ventricular diastolic time and the left ventricular systolic time as follows: ； ； = - 。 6. The control method for personalized treatment of the left ventricular assist device according to claim 1, characterized in that: The controller is designed based on the fuzzy control algorithm. The inputs of the controller are the deviation between the desired cardiac index and the feedback cardiac index and the rate of change of the deviation. The output of the controller is the current increment of the rotary pump of the left ventricular assist device.

7. The control method for personalized treatment of the left ventricular assist device according to claim 6, characterized in that: The calculation of the current increment includes: S1: Fuzzification interface; The fuzzy subsets of the deviation are divided into: Deviation = {Negative Large, Negative Medium, Negative Small, Negative Zero, Positive Zero, Positive Small, Positive Medium, Positive Large} = {NB, NM, NS, NZ, PZ, PS, PM, PB}; The fuzzy subsets of the rate of change of the deviation are divided into: Rate of change of deviation = {Negative Large, Negative Medium, Negative Small, Negative Zero, Positive Zero, Positive Small, Positive Medium, Positive Large} = {NB, NM, NS, NZ, PZ, PS, PM, PB}; The fuzzy subsets of the phase current are divided into: Phase current = {Negative Large, Negative Medium, Negative Small, Negative Zero, Positive Zero, Positive Small, Positive Medium, Positive Large} = {NB, NM, NS, NZ, PZ, PS, PM, PB}; The universes of discourse of the deviation and the rate of change of the deviation are {-6, -5, -4, -3, -2, -1, 0, 1, 2, 3, 4, 5, 6}, and the membership functions are all triangular membership functions; S2: Formulate a fuzzy rule table for the current increment based on the deviation and the rate of change of the deviation; S3: Defuzzification, using the centroid method to calculate the quantization value of the current increment, according to the following formula: ； Wherein, represents the current increment after deblurring, represents the phase current fuzzy quantity corresponding to the current increment, represents the membership value corresponding to the fuzzy quantity, is the total number of discretized output quantities.

8. The control method for personalized treatment of the left ventricular assist device according to claim 6, characterized in that: The calculation of the feedback cardiac index includes: Pump flow estimation: The expression of the pump flow estimation is as follows: ； wherein, is the estimated pump flow rate, is the rotor inertia, is the rotational speed, is the back electromotive force constant, is the current, is the damping coefficient, and are the correlation coefficients; Pump flow feature extraction: The pump flow feature extraction refers to extracting the average pump flow from the set of estimated pump flow data. The calculation formula of the average pump flow is as follows: ； wherein, is the average pump flow rate, is the total amount of samples within one cardiac cycle, and j is an index variable used to represent the sample point number within one cardiac cycle; Feedback cardiac index: The calculation formula of the feedback cardiac index is as follows: ； In the formula, is the feedback cardiac index.

9. The control method for personalized treatment of the left ventricular assist device according to claim 1, wherein: The left atrial pressure signal fed back by the physiological feedback module is the average left atrial pressure extracted by the physiological feedback module from the cardiovascular coupling system, and is calculated according to the following formula: ； wherein, is the average left atrial pressure, is the total number of samples within one cardiac cycle, and j is an index variable used to represent the sample point number within one cardiac cycle.

10. A control system for personalized treatment of a left ventricular assist device, comprising a left ventricular assist device, a cardiovascular coupling system, and a physiological feedback module, characterized in that, A control method applicable to the personalized treatment of the left ventricular assist device as described in any one of claims 1-9 includes: Starling-like regulator: Used to receive the left atrial pressure signal fed back by the physiological feedback module and output the desired cardiac index based on the patient's body surface area; Pump flow quantification feedback module: used to calculate the pump flow in real time based on the rotational speed and current of the rotary pump of the left ventricular assist device, and combine with the patient's body surface area to output the feedback cardiac index; Controller: used to determine the output current increment according to the input deviation situation; Physiological feedback module: used to receive the left atrial pressure signal of the cardiovascular coupling system and feedback it to the Starling-like regulator.

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