CN116850445A - Method, device, equipment and storage medium for controlling heart pump - Google Patents
Method, device, equipment and storage medium for controlling heart pump Download PDFInfo
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Classifications
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61M—DEVICES FOR INTRODUCING MEDIA INTO, OR ONTO, THE BODY; DEVICES FOR TRANSDUCING BODY MEDIA OR FOR TAKING MEDIA FROM THE BODY; DEVICES FOR PRODUCING OR ENDING SLEEP OR STUPOR
- A61M60/00—Blood pumps; Devices for mechanical circulatory actuation; Balloon pumps for circulatory assistance
- A61M60/50—Details relating to control
- A61M60/508—Electronic control means, e.g. for feedback regulation
- A61M60/515—Regulation using real-time patient data
- A61M60/523—Regulation using real-time patient data using blood flow data, e.g. from blood flow transducers
-
- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H40/00—ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices
- G16H40/60—ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the operation of medical equipment or devices
- G16H40/63—ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the operation of medical equipment or devices for local operation
Abstract
The embodiment of the invention discloses a heart pump control method, a device, equipment and a storage medium, wherein the method comprises the following steps: acquiring a target blood flow value of a target object; inputting the target blood flow value into a pre-trained target preload predictive model to obtain a preload predictive value; and adjusting the rotating speed of the target heart pump according to the preload predicted value and a preset preload reference standard. The technical scheme of the embodiment of the invention solves the problem of insufficient safety when the rotating speed of the heart pump is controlled by collecting the blood pressure and flow signals in the prior art, and can correspondingly adjust the rotating speed of the heart pump based on the preload predicted value of the object, thereby improving the safety in the rotating speed control process of the heart pump.
Description
Technical Field
The embodiment of the invention relates to the technical field of artificial heart control, in particular to a heart pump control method, a device, equipment and a storage medium.
Background
The heart pump is an important instrument in the transitional phase of treatment and transplantation operation of patients with severe heart failure, and the rotating speed of the heart pump is an important parameter for guaranteeing the safety of the blood circulation system of the patients. In the prior art, the rotational speed of a heart pump can be controlled by acquiring blood pressure and flow signals, determining the suction reflux degree by using a suction reflux detector and combining a preset physiological reference model. But the blood pressure and the blood flow are insufficient to intuitively reflect the pressure condition of the heart, the heart pump is regulated based on the blood pressure and the blood flow, a certain potential safety hazard exists, and dangerous events such as ventricular collapse, excessive pulmonary fluid and the like are easy to occur.
Disclosure of Invention
The embodiment of the invention provides a heart pump control method, a device, equipment and a storage medium, which can correspondingly adjust the rotating speed of a heart pump based on a preload predicted value of an object and improve the safety in the process of controlling the rotating speed of the heart pump.
In a first aspect, an embodiment of the present invention provides a method for controlling a heart pump, including:
acquiring a target blood flow value of a target object;
inputting the target blood flow value into a pre-trained target preload predictive model to obtain a preload predictive value;
and adjusting the rotating speed of the target heart pump according to the preload predicted value and a preset preload reference standard.
In a second aspect, an embodiment of the present invention provides a heart pump control device, the device comprising:
the blood flow value acquisition module is used for acquiring a target blood flow value of a target object;
the preload predictive value determining module is used for inputting the target blood flow value into a pre-trained target preload predictive model to obtain a preload predictive value;
and the heart pump rotating speed adjusting module is used for adjusting the rotating speed of the target heart pump according to the preload predicted value and a preset preload reference standard.
In a third aspect, embodiments of the present invention provide a heart pump control system, the system comprising:
a preload prediction subsystem, a heart pump rotational speed adjustment subsystem, and a heart pump;
wherein the preload prediction subsystem comprises a blood flow determination module and a preload prediction module; the blood flow determining module is used for predicting the blood flow of a target object according to the cardiovascular and heart pump coupling model and determining a target blood flow value; the preload prediction module is used for inputting the target blood flow value into a pre-trained target preload prediction model to obtain a preload predicted value, and sending the preload predicted value to the heart pump rotating speed regulating subsystem;
the heart pump rotating speed adjusting subsystem comprises a rotating speed to-be-adjusted value determining module and a heart pump rotating speed adjusting module; the rotating speed to-be-adjusted value determining module is used for determining a preload deviation value according to the preload predicted value and a preset preload reference standard and determining a heart pump rotating speed to-be-adjusted value corresponding to the preload deviation value according to the preload deviation value; the heart pump rotating speed adjusting module is used for adjusting the rotating speed of the heart pump according to the to-be-adjusted quantity of the rotating speed of the heart pump;
The heart pump comprises a physical quantity detection module, wherein the physical quantity detection module is used for detecting the rotating speed and the current of the heart pump and sending the rotating speed and the current of the heart pump to the blood flow determining module so that the blood flow determining module determines the target blood flow value based on the rotating speed and the current of the heart pump.
In a fourth aspect, an embodiment of the present invention provides a computer apparatus, including:
one or more processors;
a memory for storing one or more programs;
the one or more programs, when executed by the one or more processors, cause the one or more processors to implement the cardiac pump control method of any of the embodiments.
In a fifth aspect, embodiments of the present invention provide a computer-readable storage medium having stored thereon a computer program which, when executed by a processor, implements the heart pump control method according to any of the embodiments.
According to the technical scheme provided by the embodiment of the invention, the target blood flow value of the target object is obtained; inputting the target blood flow value into a pre-trained target preload predictive model to obtain a preload predictive value; and adjusting the rotating speed of the target heart pump according to the preload predicted value and a preset preload reference standard. The technical scheme of the embodiment of the invention solves the problem of insufficient safety when the rotating speed of the heart pump is controlled by collecting the blood pressure and flow signals in the prior art, and can correspondingly adjust the rotating speed of the heart pump based on the preload predicted value of the object, thereby improving the safety in the rotating speed control process of the heart pump.
Drawings
FIG. 1 is a flow chart of a method for controlling a heart pump according to an embodiment of the present invention;
FIG. 2 is a flow chart of yet another method for controlling a heart pump provided by an embodiment of the present invention;
FIG. 3 is a schematic structural diagram of a cardiovascular and cardiac pump coupling model according to an embodiment of the present invention;
FIG. 4 is a training flow chart of a target preload predictive model provided by an embodiment of the invention;
FIG. 5 is a flowchart of an adaptive slip-form controller for controlling the rotational speed of a heart pump according to an embodiment of the present invention;
FIG. 6 is a flowchart of an embodiment of the present invention for performing cardiac pump control;
FIG. 7 is a graph showing changes in aortic pressure values provided in accordance with an embodiment of the present invention;
FIG. 8 is a graphical representation of the change in aortic pressure values of yet another experimental set provided in accordance with an embodiment of the present invention;
FIG. 9 is a schematic diagram of a heart pump control device according to an embodiment of the present invention;
FIG. 10 is a schematic diagram of a further heart pump control device according to an embodiment of the present invention;
FIG. 11 is a schematic diagram of a heart pump control system according to an embodiment of the present invention
FIG. 12 is a schematic diagram of a still further heart pump control system provided in accordance with an embodiment of the present invention;
FIG. 13 is a flowchart of the operation of a heart pump control system provided by an embodiment of the present invention;
fig. 14 is a schematic structural diagram of a computer device according to an embodiment of the present invention.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the embodiments of the present invention more apparent, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention, and it is apparent that the described embodiments are some embodiments of the present invention, but not all embodiments of the present invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Fig. 1 is a flowchart of a method for controlling a heart pump according to an embodiment of the present invention, where the method may be implemented by a heart pump control device, and the device may be implemented by software and/or hardware.
As shown in fig. 1, the heart pump control method includes the steps of:
s110, acquiring a target blood flow value of a target object.
The target object may be, among other things, an object that requires maintenance of pressure perfusion using a heart pump and provides sufficient cardiac output. The target blood flow value may be a blood flow value required for subsequent cardiac pump control. Since the preload value is required to be solved later, and the preload value represents the load value of the left ventricle of the heart, the blood flow value of the left ventricle can be taken as the target blood flow value in order to simplify the processing steps.
Further, the blood flow value of the target object can be detected by a preset blood flow detection device, and then the target blood flow value can be obtained by obtaining the detection value of the blood flow detection device.
In addition, the blood flow of the target object can be predicted through a preset cardiovascular and heart pump coupling model, and a target blood flow value can be obtained. The components of the cardiovascular and cardiac pump coupling model comprise a left atrium, a left ventricle, an aorta, an artery, a systemic circulation, a right atrium, a right ventricle, a pulmonary artery, a pulmonary circulation, a pulmonary vein, a cardiac pump and connecting passages among the components. Different types of cardiovascular and cardiac pump coupling model structures of the target object may have different components. The cardiovascular and cardiac pump coupling model may predict a target blood flow value of the target object based on physical quantities such as rotational speed, current, etc. of the cardiac pump.
S120, inputting the target blood flow value into a pre-trained target preload prediction model to obtain a preload predicted value.
Wherein the target preload prediction model may be a model required for predicting a preload value of the target object. The preload may be the resistance or load encountered before the heart muscle contracts, i.e. the volume load or pressure experienced by the heart chamber at end diastole, the preload value being in fact the response of the ventricular end diastole volume or ventricular wall tension, in relation to the venous return volume. The preload value can more intuitively reflect the pressure condition of the heart, so that the occurrence of dangerous events such as ventricular collapse, excessive lung fluid and the like can be greatly reduced by acquiring the preload value and correspondingly controlling the rotating speed of the heart pump based on the preload value.
In view of the fact that the preload value cannot be directly detected and acquired by the detecting device, the preload predictive value can be predicted based on a target preload predictive model trained in advance. By inputting the target blood flow value to the pre-trained target preload predictive model, a predicted value of the target preload, i.e., a preload predicted value, can be obtained.
And S130, adjusting the rotating speed of the target heart pump according to the preload predicted value and a preset preload reference standard.
The preset preload reference standard may be a standard interval of preset preload values. By way of example, the preset preload reference standard for embodiments of the present invention may be 3-15mmHg. When the preload value of the target object is in the standard interval, the preload value of the target object is in a normal state, and adjustment is not needed; when the preload value of the target object is not in the standard interval, the preload value of the target object is in an abnormal state, and the rotating speed of the heart pump needs to be adjusted, so that the preload value of the target object is adjusted to be at a normal level.
The target cardiac pump may be a cardiac pump for maintaining pressure perfusion and providing cardiac output for the target subject. After the preload predictive value is obtained, the rotational speed of the target heart pump may be adjusted according to the preload predictive value and a preset preload reference standard.
Specifically, the preload predictive value may be differenced from the maximum or minimum value in the closest preset preload reference standard to determine the preload bias value; determining a preload deviation value based on the preload predicted value and a preset preload reference standard, and determining the heart pump rotating speed to be adjusted corresponding to the preload deviation value according to the corresponding relation between the preload deviation value and the heart pump rotating speed; and sending a rotation speed adjustment instruction signal to the target heart pump according to the rotation speed to-be-adjusted quantity of the heart pump so as to adjust the rotation speed of the target heart pump.
According to the technical scheme provided by the embodiment of the invention, the target blood flow value of the target object is obtained; inputting the target blood flow value into a pre-trained target preload predictive model to obtain a preload predictive value; and adjusting the rotating speed of the target heart pump according to the preload predicted value and a preset preload reference standard. The technical scheme of the embodiment of the invention solves the problem of insufficient safety when the rotating speed of the heart pump is controlled by collecting the blood pressure and flow signals in the prior art, and can correspondingly adjust the rotating speed of the heart pump based on the preload predicted value of the object, thereby improving the safety in the rotating speed control process of the heart pump.
Fig. 2 is a flowchart of another method for controlling a heart pump according to an embodiment of the present invention, where the embodiment of the present invention is applicable to a scenario in which the rotational speed of the heart pump is controlled, the embodiment further illustrates how to obtain the target blood flow value of the target object and how to adjust the rotational speed of the target heart pump according to the preload prediction value and the preset preload reference standard based on the above embodiment. The apparatus may be implemented in software and/or hardware, and integrated into a computer device having application development functionality.
As shown in fig. 2, the heart pump control method includes the steps of:
s210, constructing a cardiovascular and heart pump coupling model based on blood flow physical sign parameters of a target object.
The target object may be, among other things, a patient who needs to maintain pressure perfusion and provide adequate cardiac output using a cardiac pump. The blood flow characteristic parameter may be a parameter related to a physical characteristic of the target subject. In particular, the blood flow characterization parameters may include the closure of the mitral valve, the closure of the aortic valve, the closure of the tricuspid valve, and the closure of the pulmonary valve; mitral valve flow resistance, aortic flow resistance, systemic peripheral resistance, systemic venous resistance, tricuspid valve flow resistance, pulmonary peripheral resistance, pulmonary venous resistance; and parameters such as blood inertia of aorta and blood inertia of pulmonary artery. The blood fluid sign parameters can be set by relevant specialists according to the physical characteristics of the target object, and the accuracy of the blood fluid sign parameter values has great significance for the subsequent establishment of a cardiovascular and heart pump coupling model.
The cardiovascular and cardiac pump coupling model may be a model of the relationship between the cardiovascular circulatory system and the cardiac pump of the coupled target subject. The cardiovascular and cardiac pump coupling model may predict a blood flow value of the cardiovascular circulatory system of the target subject based on the rotational speed of the cardiac pump. Specifically, the components of the cardiovascular and cardiac pump coupling model include the left atrium, left ventricle, aorta, artery, systemic circulation, right atrium, right ventricle, pulmonary artery, pulmonary circulation, pulmonary vein, cardiac pump and the connecting passages between the components.
Fig. 3 is a schematic structural diagram of a cardiovascular and cardiac pump coupling model according to an embodiment of the present invention. As shown in fig. 3, the cardiovascular and cardiac pump coupling model includes three parts of the heart, systemic circulation, and pulmonary circulation. Wherein, the four chambers of the heart are respectively represented by separate elastic chambers; the systemic circulation part, the aorta and the artery are respectively represented by separate elastic cavities; the arterioles and the capillary network share an elastic cavity representation; veins are represented by separate elastic lumens; the lung circulation is the same.
In fig. 3, the left atrium, left ventricle, aorta, artery, systemic circulation, right atrium, right ventricle, pulmonary artery, pulmonary circulation, pulmonary vein, respectively, are anticlockwise along the direction of blood flow. The path of the uppermost part through RS from right to left back to the left atrium represents the whole body-lung circulation; the oval dashed line is the heart pump, which is connected in parallel between the left ventricle and the aorta. The most important time variable of the model is the volume characteristic of the left ventricle, reflected by a time-varying capacitance Clv (t), which is the inverse of the ventricular elasticity function E (t). Wherein P is la (t)、P lv (t)、P ao (t)、P sar (t)、P sv (t)、P ra (t)、P rv (t)、P pa (t)、P par (t)、P pv (t) represents blood pressure of left atrium, left ventricle, aorta, artery, systemic circulation, right atrium, right ventricle, pulmonary artery, pulmonary circulation, pulmonary vein, respectively; c (C) la (t)、C lv (t)、C ao (t)、C sar (t)、C sv (t)、C ra (t)、C rv (t)、C pa (t)、C par (t)、C pv (t) the compliance of the left atrium, left ventricle, aorta, artery, systemic circulation, right atrium, right ventricle, pulmonary artery, pulmonary circulation, pulmonary vein, respectively, the vessel wall being elastic, the compliance being indicative of the extent to which the vessel volume changes with changes in blood pressure; diode D mv 、D av 、D tv 、D pv Representing the mitral valve, aortic valve, tricuspid valve and pulmonary valve, respectively, with on and off representing the opening and closing of the valve, respectively; r is R mv 、R av 、R ao 、R svr 、R sv 、R tv 、R pv 、R pa 、R pvr 、R pv Mitral valve flow resistance and aorta respectivelyValve flow resistance, aortic flow resistance, systemic peripheral resistance, systemic venous resistance, tricuspid valve flow resistance, pulmonary arterial flow resistance, pulmonary peripheral resistance, pulmonary venous resistance; l (L) ao And L pa The blood inertias of the aorta and pulmonary arteries, respectively. The model of the invention comprises almost all organs of cardiovascular blood circulation, and has more authenticity and accuracy. Real-time information of blood flow, namely a dynamic graph of blood flow over time, can be obtained through the model.
S220, predicting the blood flow of the target object according to the cardiovascular and heart pump coupling model to obtain a target blood flow value.
Wherein the target blood flow value may be a blood flow value required for subsequent cardiac pump control. Since the preload value is required to be solved later, and the preload value represents the load value of the left ventricle of the heart, the blood flow value of the left ventricle can be taken as the target blood flow value in order to simplify the calculation step. Specifically, a differential equation set of three parts including heart, body circulation and lung circulation can be established, and a graph of the blood flow change with time can be obtained after the differential equation set is solved. Specifically, the differential equation set is as follows:
left core part:
right core part:
body circulation part:
part of the pulmonary circulation:
heart pump part:
wherein P represents the blood pressure (of different sites); q represents blood flow (of different sites); c represents the compliance (of different sites); r represents the blood flow resistance (of different parts); l represents the blood inertia (of different sites); h represents the inlet-outlet pressure difference of the heart pump; ω represents the rotational speed of the heart pump; beta is the kinetic coefficient of the heart pump. The differential equation set can analyze the relation among the rotation speed of the heart pump, the blood flow and the blood pressure, and lays a foundation for acquiring and subsequent processing of the real-time blood flow value. In addition, as the embodiment of the invention does not need to be implanted with a pressure sensor when acquiring the blood flow value, the risk of infection of heart failure patients is reduced.
S230, inputting the target blood flow value into a pre-trained target preload predictive model to obtain a preload predictive value.
Wherein the target preload prediction model may be a model required for predicting a preload value of the target object. The preload may be the resistance or load encountered before the heart muscle contracts, i.e. the volume load or pressure experienced by the heart chamber at end diastole, the preload value being in fact the response of the ventricular end diastole volume or ventricular wall tension, in relation to the venous return volume. The preload value can more intuitively reflect the pressure condition of the heart, so that the occurrence of dangerous events such as ventricular collapse, excessive lung fluid and the like can be greatly reduced by acquiring the preload value and correspondingly controlling the rotating speed of the heart pump based on the preload value. However, since the preload value cannot be directly detected and acquired by the detecting device, the preload predictive value can be predicted based on the target preload predictive model trained in advance. By inputting the target blood flow value to the pre-trained target preload predictive model, a predicted value of the target preload, i.e., a preload predicted value, can be obtained.
The training process of the target preload prediction model comprises the following steps: acquiring a preset blood flow sample set; inputting a preset blood flow sample set into an initial preload prediction model to obtain a preload prediction sample value; determining a model loss function value according to the preload prediction sample value and a preset preload sample value in a preset blood flow sample set, and adjusting a parameter value of the initial preload prediction model according to the model loss function value to obtain a target preload prediction model.
Fig. 4 is a training flowchart of a target preload predictive model according to an embodiment of the invention. As shown in fig. 4, the training process of the target preload prediction model includes: in a first step, a periodic heart pump blood flow signal is input as a model training sample to a heuristic peak detector for identifying peaks in heart pump blood flow. The blood flow peak value is at the inflection point of the blood flow curve, so that the change is obvious, and the blood flow peak value is used as a remarkable characteristic when the left ventricle pumps blood to the aorta, and is most suitable to be input into an initial preload prediction model as a characteristic vector. And secondly, inputting the processed samples into convolution layers, wherein the filter sizes of 4 convolution layers are 30×3, 20×3, 10×5 and 7×10 respectively, and each convolution layer comprises a batch of normalization layers. And thirdly, inputting the data processed in the second step into a maximum pooling layer, wherein the filter sizes are 7×10 and 5×10 respectively, and the step length is 2. And fourthly, inputting the data processed in the third step into two convolution layers, wherein the filter size is 3 multiplied by 10. Finally, the full connection layer with 100 and 20 neurons, the activation function of the LeakyReLU, and the missing layer with a probability of 20% were used to estimate the preload.
S240, determining a preload deviation value based on the preload predicted value and the preset preload reference standard.
The preset preload reference standard may be a standard interval of preset preload values. By way of example, the preset preload reference standard for embodiments of the present invention may be 3-15mmHg. When the preload value of the target object is in the standard interval, the preload value of the target object is in a normal state, and adjustment is not needed; when the preload value of the target object is not in the standard interval, the preload value of the target object is in an abnormal state, and the rotating speed of the heart pump needs to be adjusted, so that the preload value of the target object is adjusted to be at a normal level. The preload offset value may be an offset value of the preload predictive value from a preset preload reference standard. Specifically, the preload bias may be determined by subtracting the preload prediction from the maximum or minimum of the nearest predetermined preload references.
S250, determining the heart pump rotating speed to be adjusted corresponding to the preload deviation value according to the corresponding relation between the preload deviation value and the heart pump rotating speed.
The to-be-adjusted quantity of the rotating speed of the heart pump can be a value which needs to be adjusted. Specifically, the amount of the heart pump rotation speed to be adjusted corresponding to the preload deviation value may be determined according to the correspondence between the preload deviation value and the heart pump rotation speed. For example, the controller pseudo-order may be determined from a plurality of cardiac pump rotational speed values acquired at preset time intervals; determining a controller pseudo gradient according to the controller pseudo order and the rotation speed increment corresponding to the rotation speed values of the heart pumps; and determining the rotation speed to be adjusted of the heart pump according to the controller pseudo-order, the controller pseudo-gradient and the preload deviation value. The controller pseudo-order may be a pseudo-order of a controller that controls the rotational speed of the heart pump. The controller pseudo-gradient may be a pseudo-gradient of a controller controlling the rotational speed of the heart pump. In order to improve the control efficiency of controlling the rotational speed of the heart pump, a synovial membrane controller may be employed as the controller of the rotational speed of the heart pump.
According to the corresponding relation between the preload deviation value and the heart pump rotating speed, the step of determining the heart pump rotating speed to be adjusted corresponding to the preload deviation value is as follows:
a. determining controller pseudo-order L y And L u An input and output data sequence is constructed, and the specific formula is as follows:
wherein y (k) represents the controller output at the moment of controller k, and Δy (k) represents the increment of 2 adjacent moments thereof; u (k) represents the controller input at time k of the controller, deltau (k) represents the increment of 2 adjacent times thereof; t represents matrix transposition; l (L) y And L u Called controller pseudo-order; h Ly,Lu (k) The vector is defined according to a non-parameter dynamic linearization theory of a SISO controller, and the expression is as follows:
in the formula, deltaH Ly,Lu (k) Representing 2 adjacent moments H Ly,Lu (k) Increment vector of vector.
b. Estimating a pseudo-gradient of a controller using the following formula (a time-varying parameter vector of the controller pseudo-gradient is generally defined as Φ) f,Ly,Lu (k))：
In the method, in the process of the invention,representing an estimated value of the pseudo-gradient at time k; η represents a step size factor; μ represents a weight factor.
c. The control input delta deltau (k) is calculated by the following formula:
wherein lambda is v Representing adaptive weight factors; s (k) is a sliding mode surface, defined as s (k) =k 1 Δy(k)+k 2 e(k)，k 1 、k 2 E (k) is tracking error, e (k) =y (k) -r (k), r (k) is reference quantity; Representing a pseudo partial derivative; h is a discrete period; q 1 、q 2 And alpha is the sliding mode controller parameter, 0<q 1 h＜1，0<q 2 h＜1，0<α＜1；sig α (s(k))＝sgn(s(k))·|s(k)| α Sgn () is a sign function. Wherein Deltau (k) is the rotation speed of the heart pump to be adjusted.
And S260, sending a rotation speed adjustment instruction signal to the target heart pump according to the rotation speed to-be-adjusted quantity of the heart pump so as to adjust the rotation speed of the target heart pump.
The target cardiac pump may be a cardiac pump for maintaining pressure perfusion and providing cardiac output to a target subject, among other things. The rotation speed adjustment command signal may be a command signal for adjusting the rotation speed of the target heart pump. After the rotation speed to-be-adjusted amount of the heart pump is determined, a rotation speed adjustment instruction signal can be sent to the target heart pump according to the rotation speed to-be-adjusted amount of the heart pump so as to adjust the rotation speed of the target heart pump.
In an alternative embodiment, the motor used by the target heart pump is a bearingless permanent magnet motor, and the rotating speed control mode of the bearingless permanent magnet motor is double closed loop feedback control. Before sending a rotation speed adjustment command signal to the target heart pump, the adjustment command signal can be firstly subjected to IPARK conversion (the rotating dq coordinate system is converted into a static alpha beta coordinate system), then is sent to the inverter through space vector pulse width modulation (Space Vector Pulse Width Modulation, SVPWM), finally acts on a bearingless permanent magnet motor in the target heart pump, the bearingless permanent magnet motor rotor drives an impeller of the target heart pump to rotate so as to complete blood pumping and physiological adjustment, and finally, the preload control is completed through self-adaptive adjustment of the rotation speed.
Fig. 5 is a flowchart illustrating an operation of the adaptive sliding mode controller for controlling the rotational speed of the heart pump according to an embodiment of the present invention. As shown in fig. 5, the workflow of the adaptive sliding mode controller to control the rotational speed of the heart pump includes: firstly, carrying out difference solving processing on an estimated value of a preload and an expected value (3-15 mmHg) of the preload to obtain a deviation value, inputting the deviation value into a controller, carrying out difference solving processing on the deviation value and the expected value (3-15 mmHg) of the preload to obtain a deviation value, inputting the deviation value into the controller as a reference input, obtaining a control input through calculation of the controller (built-in model formula), transmitting the control input into a heart pump motor to control the rotating speed of the heart pump motor, and simultaneously, feeding real-time rotating speed information output by the heart pump back into the control to form closed-loop control so as to ensure that the preload is controlled within the expected value (3-15 mmHg) in real time. The invention adopts the model-free parameter self-adaptive sliding mode controller to realize the control of the preload, and has simpler structure, reduced calculation load and calculation time and improved response speed of the system compared with other self-adaptive controllers (such as an artificial neural network and a fuzzy controller).
Illustratively, FIG. 6 is a flowchart of an embodiment of the present invention for performing cardiac pump control. As shown in fig. 6, the workflow for performing heart pump control includes: the first step: establishing a cardiovascular system and heart pump coupling model; and a second step of: designing a deep convolutional neural network to obtain a preload estimated value; and a third step of: designing a model-free parameter self-adaptive sliding mode controller, and importing an estimated value and an expected value of a preload into the controller; fourth step: the controller processes the calculation and then sends out a pump rotation speed adjustment instruction, and changes the rotation speed so that the preload value can track the expected value.
In order to verify the effectiveness of the technical scheme provided by the embodiment of the invention, the embodiment of the invention is based on the heart pump control method. Fig. 7 is a schematic diagram illustrating a change of the aortic pressure value according to an embodiment of the present invention. The control method and the cardiovascular and heart pump coupling system model are made into a simulation model through Simulink modeling and m-file coding. After the parameters are set, a simulation model is operated to obtain the hemodynamic condition and the change condition of the preload of the heart pump along with time and the rotation speed of the pump, wherein the hemodynamic condition is represented by the cardiovascular important index, namely the arterial pressure, and the heart rate and the heart output are not analyzed. The results of the aortic pressure are shown in fig. 7, and when heart failure heart is inserted into the heart pump of the control method of the invention, the range of the aortic pressure is 88-119 mmHg, and the average aortic pressure is basically kept near 100mmHg, and the average aortic pressure is in the normal physiological range, which indicates that the heart pump adopting the control method of the invention can assist the patient of the damaged heart to obtain sufficient blood perfusion.
Fig. 8 is a graph showing the variation of aortic pressure values of yet another experimental group provided in accordance with an embodiment of the present invention. As shown in fig. 8, in order to highlight the effect of the estimation of the preload, a set of measurement experiments was added for comparison. Meanwhile, in order to verify the reaction of the method in coping with different states of a patient, the process is divided into two sections by modifying partial parameter values of a cardiovascular system and heart pump coupling model, wherein the first half section is in a motion state, and the second half section is converted into a resting state. As can be seen from fig. 8, in the first half, the estimated value and the measured value of the preload are basically coincident, which indicates that the estimation effect of the deep convolutional neural network model is very good, and the speed of the heart pump fluctuates in a small range to maintain the preload; after the motion state is changed into the resting state, the estimated curve of the preload relative to the measured curve has a certain amplitude fluctuation, but the preload value can still be controlled within the range of 3-15mmHg, the fluctuation is regulated briefly and then stably tracks the measured curve, the rotation speed of the heart pump is kept stable after the modulation is finished for keeping the preload continuously falling, and the method has strong regulation capability when dealing with emergency. In summary, the method of the invention can accurately control the preload value within the range of 3-15mmHg, and can adjust along with the change of the state of a patient, thereby effectively avoiding the occurrence of aspiration and pulmonary hemorrhage under different states, maintaining sufficient blood perfusion and improving the life quality of patients with heart failure.
According to the technical scheme provided by the embodiment of the invention, a cardiovascular and heart pump coupling model is constructed based on the blood flow physical sign parameters of the target object; predicting the blood flow of the target object according to the cardiovascular and heart pump coupling model to obtain a target blood flow value; inputting the target blood flow value into a pre-trained target preload predictive model to obtain a preload predictive value; determining a preload offset value based on the preload predictive value and a preset preload reference standard; determining the heart pump rotating speed to be adjusted corresponding to the preload deviation value according to the corresponding relation between the preload deviation value and the heart pump rotating speed; and sending a rotation speed adjustment instruction signal to the target heart pump according to the rotation speed to-be-adjusted quantity of the heart pump so as to adjust the rotation speed of the target heart pump. The technical scheme of the embodiment of the invention solves the problem of insufficient safety when the rotating speed of the heart pump is controlled by collecting the blood pressure and flow signals in the prior art, and can correspondingly adjust the rotating speed of the heart pump based on the preload predicted value of the object, thereby improving the safety in the rotating speed control process of the heart pump.
Fig. 9 is a schematic structural diagram of a heart pump control device according to an embodiment of the present invention, where the embodiment of the present invention is applicable to a scenario in which the rotational speed of a heart pump is controlled, and the device may be implemented in a software and/or hardware manner, and integrated into a computer device with an application development function.
As shown in fig. 9, the heart pump control device includes: a blood flow value acquisition module 310, a preload predictive value determination module 320, and a heart pump rotational speed adjustment module 330.
The blood flow value acquisition module is used for acquiring a target blood flow value of a target object; the preload predictive value determining module is used for inputting the target blood flow value into a pre-trained target preload predictive model to obtain a preload predictive value; and the heart pump rotating speed adjusting module is used for adjusting the rotating speed of the target heart pump according to the preload predicted value and the preset preload reference standard.
According to the technical scheme provided by the embodiment of the invention, the target blood flow value of the target object is obtained; inputting the target blood flow value into a pre-trained target preload predictive model to obtain a preload predictive value; and adjusting the rotating speed of the target heart pump according to the preload predicted value and a preset preload reference standard. The technical scheme of the embodiment of the invention solves the problem of insufficient safety when the rotating speed of the heart pump is controlled by collecting the blood pressure and flow signals in the prior art, and can correspondingly adjust the rotating speed of the heart pump based on the preload predicted value of the object, thereby improving the safety in the rotating speed control process of the heart pump.
In an alternative embodiment, the blood flow value acquisition module 310 is specifically configured to: constructing a cardiovascular and cardiac pump coupling model based on blood flow physical sign parameters of a target object; and predicting the blood flow of the target object according to the cardiovascular and heart pump coupling model to obtain a target blood flow value.
In an alternative embodiment, the components of the cardiovascular and cardiac pump coupling model include the left atrium, left ventricle, aorta, artery, systemic circulation, right atrium, right ventricle, pulmonary artery, pulmonary circulation, pulmonary veins, cardiac pumps, and the connecting pathways between the components.
In an alternative embodiment, heart pump rotational speed adjustment module 330 is specifically configured to: determining a preload offset value based on the preload predictive value and a preset preload reference standard; determining the heart pump rotating speed to be adjusted corresponding to the preload deviation value according to the corresponding relation between the preload deviation value and the heart pump rotating speed; and sending a rotation speed adjustment instruction signal to the target heart pump according to the rotation speed to-be-adjusted quantity of the heart pump so as to adjust the rotation speed of the target heart pump.
In an alternative embodiment, heart pump rotational speed adjustment module 330 is specifically configured to: determining a controller pseudo-order according to a plurality of heart pump rotating speed values acquired at preset time intervals; determining a controller pseudo gradient according to the controller pseudo order and the rotation speed increment corresponding to the rotation speed values of the heart pumps; and determining the rotation speed to be adjusted of the heart pump according to the controller pseudo-order, the controller pseudo-gradient and the preload deviation value.
In an alternative embodiment, the heart pump control device further comprises: the preload prediction model training module is used for: acquiring a preset blood flow sample set; inputting a preset blood flow sample set into an initial preload prediction model to obtain a preload prediction sample value; determining a model loss function value according to the preload prediction sample value and a preset preload sample value in a preset blood flow sample set, and adjusting a parameter value of the initial preload prediction model according to the model loss function value to obtain a target preload prediction model.
To verify the feasibility of the above method, fig. 10 is an exemplary schematic structural diagram of still another heart pump control device according to an embodiment of the present invention. As shown in fig. 10, the control device includes a system monitoring interface, a cardiovascular simulator, a computer, a controller, a drive board, a heart pump, a flowmeter, a pressure sensor, a resistance regulator, and a piping for connection. The controller of the device comprises the control method and the system provided by the invention, and the hemodynamic information can be obtained after the control device and the independently developed heart pump are started, so that the preliminary verification of the clinical application of the heart pump and the control method of the invention is completed.
The heart pump control device provided by the embodiment of the invention can execute the heart pump control method provided by any embodiment of the invention, and has the corresponding functional modules and beneficial effects of the execution method.
Fig. 11 is a schematic structural diagram of a heart pump control system according to an embodiment of the present invention, where the embodiment of the present invention is applicable to a scenario in which the rotational speed of a heart pump is controlled, and the device may be implemented by software and/or hardware, and integrated into a computer device with an application development function.
As shown in fig. 11, the heart pump control system includes: a preload prediction subsystem, a heart pump rotational speed adjustment subsystem, and a heart pump.
Wherein the preload prediction subsystem comprises a blood flow determination module and a preload prediction module; the blood flow determining module is used for predicting the blood flow of the target object according to the cardiovascular and heart pump coupling model and determining a target blood flow value; the preload prediction module is used for inputting the target blood flow value into a pre-trained target preload prediction model to obtain a preload predicted value, and sending the preload predicted value to the heart pump rotating speed regulating subsystem.
The heart pump rotating speed adjusting subsystem comprises a rotating speed to-be-adjusted value determining module and a heart pump rotating speed adjusting module; the rotating speed to-be-adjusted value determining module is used for determining a preload deviation value according to the preload predicted value and a preset preload reference standard and determining a heart pump rotating speed to-be-adjusted value corresponding to the preload deviation value according to the preload deviation value; the heart pump rotating speed adjusting module is used for adjusting the rotating speed of the heart pump according to the to-be-adjusted quantity of the rotating speed of the heart pump.
The heart pump includes a physical quantity detection module, wherein the physical quantity detection module is configured to detect a rotational speed and a current of the heart pump and send the rotational speed and the current of the heart pump to the blood flow determination module, such that the blood flow determination module determines a target blood flow value based on the rotational speed and the current of the heart pump.
Fig. 12 is a schematic structural view of yet another heart pump control system according to an embodiment of the present invention. As shown in fig. 12, the heart pump control system includes a detection module, a calculation module, and an execution module. The detection module comprises a cardiovascular circulatory system and heart pump coupling model and a deep convolution neural network model, wherein the deep convolution neural network model is used for detecting and estimating a blood flow curve chart output by the cardiovascular circulatory system and heart pump coupling model; the calculation module comprises a model-free parameter self-adaptive sliding mode controller and input and output, and is used for accurately controlling a preload value; the execution module comprises a heart pump and is used for receiving a control instruction sent by the model-free parameter self-adaptive sliding mode controller and completing the modulation of the rotation speed of the pump.
Illustratively, FIG. 13 is a flowchart of the operation of a heart pump control system provided by an embodiment of the present invention. As shown in fig. 13, the workflow of the heart pump control system includes: firstly, the rotating speed and the current of a bearingless permanent magnet motor for a heart pump are acquired, the rotating speed and the current are input into a cardiovascular system and heart pump coupling model, a blood flow curve is acquired, then the blood flow curve is input into a deep convolutional neural network to conduct preload value prediction, a preload estimated value is obtained, then a model-free parameter self-adaptive sliding mode controller determines a rotating speed adjusting signal based on the preload expected value and the preload estimated value, IPARK conversion is conducted on the rotating speed adjusting signal, then the signal subjected to the IPARK conversion is subjected to signal processing through an SVPWM module and an inverter in sequence, and finally the processed signal is sent to the bearingless permanent magnet motor for the heart pump, so that the bearingless permanent magnet motor can adjust the rotating speed of the heart pump. And by analogy, the control of the rotating speed of the heart pump is continuously realized by acquiring the rotating speed and the current of the bearingless permanent magnet motor for the heart pump.
Fig. 14 is a schematic structural diagram of a computer device according to an embodiment of the present invention. FIG. 14 illustrates a block diagram of an exemplary computer device 12 suitable for use in implementing embodiments of the present invention. The computer device 12 shown in fig. 14 is only an example and should not be construed as limiting the functionality and scope of use of embodiments of the invention. The computer device 12 may be any terminal device with computing power and may be configured in a heart pump control device.
As shown in FIG. 14, the computer device 12 is in the form of a general purpose computing device. Components of computer device 12 may include, but are not limited to: one or more processors or processing units 16, a system memory 28, a bus 18 that connects the various system components, including the system memory 28 and the processing units 16.
Bus 18 may be one or more of several types of bus structures including a memory bus or memory controller, a peripheral bus, an accelerated graphics port, a processor, or a local bus using any of a variety of bus architectures. By way of example, and not limitation, such architectures include Industry Standard Architecture (ISA) bus, micro channel architecture (MAC) bus, enhanced ISA bus, video Electronics Standards Association (VESA) local bus, and Peripheral Component Interconnect (PCI) bus.
Computer device 12 typically includes a variety of computer system readable media. Such media can be any available media that is accessible by computer device 12 and includes both volatile and nonvolatile media, removable and non-removable media.
The system memory 28 may include computer system readable media in the form of volatile memory, such as Random Access Memory (RAM) 30 and/or cache memory 32. The computer device 12 may further include other removable/non-removable, volatile/nonvolatile computer system storage media. By way of example only, storage system 34 may be used to read from or write to non-removable, nonvolatile magnetic media (not shown in FIG. 14, commonly referred to as a "hard disk drive"). Although not shown in fig. 14, a magnetic disk drive for reading from and writing to a removable non-volatile magnetic disk (e.g., a "floppy disk"), and an optical disk drive for reading from or writing to a removable non-volatile optical disk (e.g., a CD-ROM, DVD-ROM, or other optical media) may be provided. In such cases, each drive may be coupled to bus 18 through one or more data medium interfaces. The system memory 28 may include at least one program product having a set (e.g., at least one) of program modules configured to carry out the functions of the embodiments of the invention.
A program/utility 40 having a set (at least one) of program modules 42 may be stored in, for example, system memory 28, such program modules 42 including, but not limited to, an operating system, one or more application programs, other program modules, and program data, each or some combination of which may include an implementation of a network environment. Program modules 42 generally perform the functions and/or methods of the embodiments described herein.
The computer device 12 may also communicate with one or more external devices 14 (e.g., keyboard, pointing device, display 24, etc.), one or more devices that enable a user to interact with the computer device 12, and/or any devices (e.g., network card, modem, etc.) that enable the computer device 12 to communicate with one or more other computing devices. Such communication may occur through an input/output (I/O) interface 22. Moreover, computer device 12 may also communicate with one or more networks such as a Local Area Network (LAN), a Wide Area Network (WAN) and/or a public network, such as the Internet, through network adapter 20. As shown, network adapter 20 communicates with other modules of computer device 12 via bus 18. It should be appreciated that although not shown in fig. 14, other hardware and/or software modules may be used in connection with computer device 12, including, but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, data backup storage systems, and the like.
The processing unit 16 executes various functional applications and data processing by running programs stored in the system memory 28, for example, implementing the heart pump control method provided by the embodiment of the present invention, the method includes:
acquiring a target blood flow value of a target object;
inputting the target blood flow value into a pre-trained target preload predictive model to obtain a preload predictive value;
and adjusting the rotating speed of the target heart pump according to the preload predicted value and a preset preload reference standard.
The present embodiment provides a computer-readable storage medium having stored thereon a computer program which, when executed by a processor, implements the heart pump control method as provided by any embodiment of the present invention, comprising:
acquiring a target blood flow value of a target object;
inputting the target blood flow value into a pre-trained target preload predictive model to obtain a preload predictive value;
and adjusting the rotating speed of the target heart pump according to the preload predicted value and a preset preload reference standard.
The computer storage media of embodiments of the invention may take the form of any combination of one or more computer-readable media. The computer readable medium may be a computer readable signal medium or a computer readable storage medium. The computer readable storage medium may be, for example, but not limited to: an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or a combination of any of the foregoing. More specific examples (a non-exhaustive list) of the computer-readable storage medium would include the following: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In this document, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device.
The computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, either in baseband or as part of a carrier wave. Such a propagated data signal may take any of a variety of forms, including, but not limited to, electro-magnetic, optical, or any suitable combination of the foregoing. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device.
Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to: wireless, wire, fiber optic cable, RF, etc., or any suitable combination of the foregoing.
Computer program code for carrying out operations of the present invention may be written in one or more programming languages, including an object oriented programming language such as Java, smalltalk, C ++ and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any kind of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or may be connected to an external computer (for example, through the Internet using an Internet service provider).
It will be appreciated by those of ordinary skill in the art that the modules or steps of the invention described above may be implemented in a general purpose computing device, they may be centralized on a single computing device, or distributed over a network of computing devices, or they may alternatively be implemented in program code executable by a computer device, such that they are stored in a memory device and executed by the computing device, or they may be separately fabricated as individual integrated circuit modules, or multiple modules or steps within them may be fabricated as a single integrated circuit module. Thus, the present invention is not limited to any specific combination of hardware and software.
Note that the above is only a preferred embodiment of the present invention and the technical principle applied. It will be understood by those skilled in the art that the present invention is not limited to the particular embodiments described herein, but is capable of various obvious changes, rearrangements and substitutions as will now become apparent to those skilled in the art without departing from the scope of the invention. Therefore, while the invention has been described in connection with the above embodiments, the invention is not limited to the embodiments, but may be embodied in many other equivalent forms without departing from the spirit or scope of the invention, which is set forth in the following claims.
Claims (10)
1. A method of controlling a heart pump, comprising:
acquiring a target blood flow value of a target object;
inputting the target blood flow value into a pre-trained target preload predictive model to obtain a preload predictive value;
and adjusting the rotating speed of the target heart pump according to the preload predicted value and a preset preload reference standard.
2. The method of claim 1, wherein the obtaining a target blood flow value of the target object comprises:
constructing a cardiovascular and cardiac pump coupling model based on blood flow sign parameters of the target object;
and predicting the blood flow of the target object according to the cardiovascular and heart pump coupling model to obtain the target blood flow value.
3. The method of claim 2, wherein the components of the cardiovascular and cardiac pump coupling model include a left atrium, a left ventricle, an aorta, an artery, a systemic circulation, a right atrium, a right ventricle, a pulmonary artery, a pulmonary circulation, a pulmonary vein, a cardiac pump, and a connection between the components.
4. The method of claim 1, wherein adjusting the rotational speed of the target heart pump based on the preload prediction and a preset preload reference criteria comprises:
Determining a preload offset value based on the preload predictive value and the preset preload reference standard;
determining the heart pump rotating speed to be adjusted corresponding to the preload deviation value according to the corresponding relation between the preload deviation value and the heart pump rotating speed;
and sending a rotation speed adjustment instruction signal to the target heart pump according to the rotation speed to-be-adjusted quantity of the heart pump so as to adjust the rotation speed of the target heart pump.
5. The method according to claim 4, wherein determining the heart pump rotational speed to be adjusted corresponding to the preload deviation value according to the correspondence between the preload deviation value and the heart pump rotational speed includes:
determining a controller pseudo-order according to a plurality of heart pump rotating speed values acquired at preset time intervals;
determining a controller pseudo gradient according to the controller pseudo order and the rotation speed increment corresponding to the plurality of heart pump rotation speed values;
and determining the rotation speed to be adjusted of the heart pump according to the controller pseudo-order, the controller pseudo-gradient and the preload deviation value.
6. The method of claim 1, wherein the training process of the target preload predictive model comprises:
Acquiring a preset blood flow sample set;
inputting the preset blood flow sample set into an initial preload prediction model to obtain a preload prediction sample value;
determining a model loss function value according to the preload prediction sample value and a preset preload sample value in a preset blood flow sample set, and adjusting a parameter value of the initial preload prediction model according to the model loss function value to obtain the target preload prediction model.
7. A heart pump control device provided in a vehicle terminal, comprising:
the blood flow value acquisition module is used for acquiring a target blood flow value of a target object;
the preload predictive value determining module is used for inputting the target blood flow value into a pre-trained target preload predictive model to obtain a preload predictive value;
and the heart pump rotating speed adjusting module is used for adjusting the rotating speed of the target heart pump according to the preload predicted value and a preset preload reference standard.
8. A heart pump control system, the system comprising:
a preload prediction subsystem, a heart pump rotational speed adjustment subsystem, and a heart pump;
wherein the preload prediction subsystem comprises a blood flow determination module and a preload prediction module; the blood flow determining module is used for predicting the blood flow of a target object according to the cardiovascular and heart pump coupling model and determining a target blood flow value; the preload prediction module is used for inputting the target blood flow value into a pre-trained target preload prediction model to obtain a preload predicted value, and sending the preload predicted value to the heart pump rotating speed regulating subsystem;
The heart pump rotating speed adjusting subsystem comprises a rotating speed to-be-adjusted value determining module and a heart pump rotating speed adjusting module; the rotating speed to-be-adjusted value determining module is used for determining a preload deviation value according to the preload predicted value and a preset preload reference standard and determining a heart pump rotating speed to-be-adjusted value corresponding to the preload deviation value according to the preload deviation value; the heart pump rotating speed adjusting module is used for adjusting the rotating speed of the heart pump according to the to-be-adjusted quantity of the rotating speed of the heart pump;
the heart pump comprises a physical quantity detection module, wherein the physical quantity detection module is used for detecting the rotating speed and the current of the heart pump and sending the rotating speed and the current of the heart pump to the blood flow determining module so that the blood flow determining module determines the target blood flow value based on the rotating speed and the current of the heart pump.
9. A server device, characterized in that the server device comprises:
one or more processors;
a memory for storing one or more programs;
the one or more programs, when executed by the one or more processors, cause the one or more processors to implement the cardiac pump control method of any one of claims 1-6.
10. A computer-readable storage medium, on which a computer program is stored, characterized in that the program, when being executed by a processor, implements a heart pump control method as claimed in any one of claims 1-6.
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