An intelligent physiological control system for artificial hearts

Abstract

An artificial heart intelligent physiological control system belongs to the field of biomedical engineering and comprises an electromechanical physiological parameter detection module, a heart function evaluation module, a vascular biomechanics evaluation module and an intelligent physiological decision module.The electromechanical physiological parameter detection module is used for detecting electromechanical signals of the artificial heart and physiological signals of a patient, the heart function evaluation module is used for calculating a heart function index of the patient, the vascular biomechanics evaluation module is used for calculating a blood rotation index, and the intelligent physiological decision module takes the two indexes as control inputs, determines a working rotating speed of the artificial heart according to real-time states of the patient and the artificial heart, and adjusts the working rotating speed through an artificial heart driving module.The control strategy can ensure stable working of the artificial heart, quickly respond to abnormal events such as ventricular suction, excessive unloading and pulmonary congestion, and determine an artificial heart working level that is most beneficial to recovery of the heart function of the patient and maintenance of normal functions of blood vessels.

Description

Technical Field

[0001] This invention relates to an intelligent physiological control system for an artificial heart, belonging to the field of biomedical engineering. Background Technology

[0002] Artificial hearts are crucial medical devices for treating critical cardiovascular diseases and saving the lives of patients with heart failure. Whether their operation is adapted to the patient's physiological state directly determines the therapeutic effect and long-term prognosis. The performance of the control system is a key factor in determining the clinical auxiliary effect of artificial hearts. To improve the clinical efficacy of artificial hearts, researchers have conducted systematic research on artificial heart controllers. Li Junjie et al. proposed a biomedical engineering-based intelligent control system and method for artificial hearts (CN202210266278), which can automatically adjust the rotation speed of the artificial heart according to the patient's physiological parameters. However, this controller requires pre-setting the ideal physiological parameter range for the patient, and the physiological parameters of most critically ill cardiovascular patients deviate from normal values, making it difficult to achieve ideal control effects. The Institute of Electrical Engineering, Chinese Academy of Sciences, proposed a sensorless control method for the motor of an artificial heart pump (CN202210196151), which can achieve closed-loop control of the artificial heart by observing the rotor position. However, the input parameters of this controller do not include the patient's physiological parameters, therefore it cannot respond correctly to changes in the patient's physiological state. The artificial heart control system and operation method based on IoT edge computing proposed by Beijing University of Technology (CN202011391615) combines artificial intelligence algorithms with the real-time control of the artificial heart through IoT and edge computing methods. However, the control system does not take into account the long-term interaction between the artificial heart and the patient, and therefore cannot create the best environment for the recovery of the patient's heart function. Summary of the Invention

[0003] In order to meet the long-term clinical needs of artificial hearts, and to respond quickly and effectively to various complications that patients may experience during use, such as ventricular aspiration, excessive cardiac unloading, and pulmonary congestion, this invention provides an intelligent physiological control system for artificial hearts that adjusts the working state of the artificial heart according to changes in the patient's heart and blood vessel function. This system creates the best environment for the recovery of the patient's heart function and ensures the normal function of blood vessels.

[0004] To achieve the above objectives, the present invention adopts the following technical solution: an intelligent physiological control system for an artificial heart, comprising an electrophysiological parameter detection module, a cardiac function assessment module, a vascular biomechanical assessment module, an intelligent physiological decision-making module, and a drive module for the artificial heart, characterized in that:

[0005] The electromechanical physiological parameter detection module can collect and detect electromechanical signals and the patient's physiological parameters during the operation of the artificial heart;

[0006] The cardiac function assessment module evaluates the patient's current cardiac function index based on the patient's physiological parameters;

[0007] The vascular biomechanical assessment module calculates the blood flow vortex index based on the collected electromechanical signals;

[0008] The intelligent physiological decision-making module can make decisions based on changes in cardiac function index and blood flow vortex index to determine the optimal working level of the artificial heart; thereby determining the current set rotation speed value of the artificial heart; and then adjusting the working current and rotor speed of the artificial heart accordingly.

[0009] Preferably, the patient's physiological parameters include the patient's mean arterial pressure, cardiac cycle, electrocardiogram (ECG) signal, and cardiac output data. The patient's cardiac cycle signal is extracted from the ECG signal and its change over time is calculated. The mean arterial pressure signal and cardiac output signal are used to calculate the change of mean arterial pressure over time.

[0010] Preferably, the cardiac function assessment module is based on the formula:

[0011]

[0012] t c Heartbeat Cycle

[0013] t — time

[0014] MAP—Mean Arterial Pressure

[0015] BRS – Heart Function Index.

[0016] Preferably, the electromechanical signals include: the rotational speed of the artificial heart, the output blood flow rate, the inlet and outlet pressure difference of the artificial heart, the rotor vibration amplitude, and the input current. The spatial distribution of blood flow velocity output by the blood pump in the blood vessel is calculated based on the rotational speed of the artificial heart, the output blood flow rate, the inlet and outlet pressure difference of the artificial heart, the rotor vibration amplitude, and the input current. The blood flow vortex distribution is calculated based on the spatial distribution of blood flow velocity, and then the blood flow vortex intensity in the blood vessel is calculated based on the blood flow velocity and blood flow vortex, and characterized by the blood flow vortex index.

[0017] Preferably, the vascular biomechanical assessment module is based on the formula:

[0018]

[0019]

[0020]

[0021] U - Blood flow velocity

[0022] ω - Blood flow vorticity

[0023] t - Time

[0024] P - Blood pressure

[0025] ρ - Blood density

[0026] μ t - Turbulent viscosity of blood

[0027] LNH - Blood flow swirling index.

[0028] Preferably, the intelligent physiological decision - making module has a three - layer serial decision - making structure:

[0029] The outer layer is the functional state decision - making layer, which judges whether the cardiac function and aortic vascular function of the current patient are in the optimal state according to the results of the cardiac function evaluation module and the vascular biomechanics evaluation module. If the deviation from the optimal state exceeds the set threshold, it makes adjustments to the working level of the artificial heart. The working level of the artificial heart includes the optimal working speed, the optimal working torque and the optimal input power of the artificial heart;

[0030] The middle layer is the physiological state decision - making layer, which takes the working level of the artificial heart determined by the functional decision - making layer as the input, calculates the unloading level of the artificial heart according to the electromechanical signals such as the pressure difference between the inlet and outlet of the artificial heart, the output blood flow, and the input current level. The unloading level is measured by the BAI index. When abnormal physiological states such as ventricular suction (BAI > 100%), over - unloading (80% < BAI < 100%) or pulmonary congestion (BAI < 20%) occur, the control strategy of this layer makes a timely response and adjusts the current set speed of the artificial heart;

[0031] The inner layer is the electromechanical state decision - making layer, which takes the current set speed of the artificial heart determined by the functional state decision - making layer as the input signal, constructs an actual state observer of the artificial heart according to the actual speed, input current and rotor vibration amplitude signal of the artificial heart. When the actual electromechanical state deviates from the ideal state, the control strategy of this layer actively adjusts the working current and rotor speed to ensure the stability and reliability of the operation of the artificial heart electromechanical system.

[0032] Preferably, the intelligent physiological decision - making module - the functional decision - making layer is based on the formula:

[0033]

[0034] x1 - Tracking signal of the input signal

[0035] v(k) - Input signal

[0036] x2 — the derivative of the input signal

[0037] γ—Functional decision layer algorithm tracking convergence speed variable

[0038] h — Integral step size.

[0039] Preferably, the intelligent physiological decision-making module—the physiological state decision-making layer—is based on the following formula:

[0040]

[0041]

[0042]

[0043] BAI – Unloading Level of Artificial Heart

[0044] u(k) — The current set rotational speed of the artificial heart.

[0045] The beneficial effects of this invention are:

[0046] (1) The physiological state decision layer algorithm of the present invention uses non-parametric model adaptive control theory to construct the control rate and takes the ventricular unloading level of the artificial heart as the control variable. When it is found that the actual ventricular unloading level deviates too much from the preset value, the working speed of the artificial heart will be adjusted.

[0047] (2) When the decision module determines the working speed of the artificial heart based on the real-time working status of the patient and the artificial heart, it will send the working speed to the drive module. The drive module will adjust the stator magnetic field of the artificial heart to achieve speed adjustment of the response.

[0048] (3) The intelligent physiological control strategy of the present invention determines the optimal working state for promoting cardiac function recovery and maintaining normal vascular function by searching for the extreme values ​​of cardiac function index and blood flow vortex index.

[0049] (4) The intelligent physiological control strategy of the present invention adopts a non-parametric model adaptive control strategy to construct a physiological state decision algorithm, and adjusts the unloading level of the artificial heart according to the adjustment. Attached Figure Description

[0050] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0051] Figure 1This invention relates to an intelligent physiological control system for an artificial heart. Detailed Implementation

[0052] The features and advantages of this application will become clearer and more explicit through the following detailed description.

[0053] In the description of this application, it should be noted that the terms "upper," "lower," "inner," "outer," "front," "rear," "left," and "right," etc., indicate the orientation or positional relationship based on the orientation or positional relationship in the working state of this application, and are only for the convenience of describing this application and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation on this application. In addition, the terms "first," "second," "third," and "fourth" are used for descriptive purposes only and should not be construed as indicating or implying relative importance.

[0054] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0055] This application provides an intelligent physiological control system for an artificial heart. The system includes an electromechanical-physiological parameter detection module, a cardiac function assessment module, a vascular biomechanical assessment module, an intelligent physiological decision-making module, and an artificial heart drive module. First, the electromechanical-physiological parameter acquisition module collects and detects mechanical and electronic signals and the patient's physiological parameters during the artificial heart's operation, mainly including: the artificial heart's rotational speed, output blood flow, inlet and outlet pressure difference, rotor vibration amplitude, input current, mean arterial pressure, heart rate, electrocardiogram, and cardiac output data. Subsequently, it sends the above data to the cardiac function assessment module and the vascular biomechanical assessment module. These two modules calculate the cardiac unloading index and blood flow vortex index, respectively. Then, the intelligent physiological decision-making module uses these two indices as input indicators and, based on the artificial heart's working state and the patient's physiological state, employs a serial hierarchical decision-making method to make decisions regarding the patient's cardiac and vascular state, the cardiac unloading state, and the artificial heart's working state, ultimately determining the artificial heart's operating rotational speed and sending it to the artificial heart drive module. Finally, the artificial heart drive module adjusts the rotational speed and phase of the magnetic field of the stator inside the artificial heart to regulate the artificial heart's operating rotational speed.

[0056] This system can be implemented using a computer or embedded device, and can achieve intelligent control of the artificial heart by writing programs.

[0057] Through in vitro and animal experiments, the controller can adjust to changes in cardiac and vascular function in experimental animals. The adjustment speed for cardiac and vascular function is less than 0.5 hours, the response speed for adverse events such as cardiac aspiration, excessive unloading, and pulmonary congestion is less than 60 seconds, and the response time for disturbances in the electromechanical system parameters of the artificial heart is less than 100 ms.

[0058] Figure 1 This invention relates to an intelligent physiological control system for an artificial heart; the following is in conjunction with the appendix. Figure 1 The following embodiments further illustrate the present invention, but the present invention is not limited to the following embodiments.

[0059] Example 1

[0060] An intelligent physiological control system for an artificial heart includes an electrophysiological parameter detection module, a cardiac function assessment module, a vascular biomechanical assessment module, an intelligent physiological decision-making module, and a drive module for the artificial heart.

[0061] The electromechanical physiological parameter detection module can collect and detect electromechanical signals and the patient's physiological parameters during the operation of the artificial heart;

[0062] The cardiac function assessment module evaluates the patient's current cardiac function index based on the patient's physiological parameters;

[0063] The vascular biomechanical assessment module calculates the blood flow vortex index based on the collected electromechanical signals;

[0064] The intelligent physiological decision-making module can make decisions based on changes in cardiac function index and blood flow vortex index to determine the optimal working level of the artificial heart; thereby determining the current set rotational speed of the artificial heart; and then adjusting the working current and rotor speed of the artificial heart accordingly.

[0065] In this embodiment, the patient's physiological parameters include the patient's mean arterial pressure, cardiac cycle, electrocardiogram (ECG) signal, and cardiac output data. The patient's cardiac cycle signal is extracted from the ECG signal and its change over time is calculated. The mean arterial pressure signal and cardiac output signal are used to calculate the change of mean arterial pressure over time.

[0066] In this embodiment, the cardiac function assessment module is based on the formula:

[0067]

[0068] t c Heartbeat Cycle

[0069] t — time

[0070] MAP—Mean Arterial Pressure

[0071] BRS – Heart Function Index.

[0072] The cardiac function index is an indicator of a patient's cardiac contractile function; a higher value indicates better current cardiac function. Therefore, the control objective of the outer layer strategy is to adjust the working level of the artificial heart so that the patient's cardiac function index is always near its maximum value. Based on clinical experience with most healthy individuals, the optimal range for the cardiac function index is determined to be between 10 and 12.5.

[0073] In this embodiment, the electromechanical signals include: the rotational speed of the artificial heart, the output blood flow rate, the inlet and outlet pressure difference of the artificial heart, the rotor vibration amplitude, and the input current. The spatial distribution of blood flow velocity output by the blood pump in the blood vessel is calculated based on the rotational speed of the artificial heart, the output blood flow rate, the inlet and outlet pressure difference of the artificial heart, the rotor vibration amplitude, and the input current. The blood flow vortex distribution is calculated based on the spatial distribution of blood flow velocity, and then the blood flow vortex intensity in the blood vessel is calculated based on the blood flow velocity and blood flow vortex, and is characterized by the blood flow vortex index.

[0074] In this embodiment, the vascular biomechanical assessment module is based on the formula:

[0075]

[0076]

[0077]

[0078] U - Blood Flow Velocity

[0079] ω——Blood flow vortex

[0080] t—time

[0081] P—Blood pressure

[0082] ρ—blood density

[0083] μ t —Blood turbulent viscosity

[0084] LNH – Blood Flow Rotation Index.

[0085] The blood flow vortex index is an indicator of the intensity of blood vortexing in the aorta. The normal vortex index range in the human aorta is 0.2-0.8. Therefore, the control objective of the outer layer control strategy is to ensure that the blood flow vortex index in the aorta remains within this range.

[0086] In this embodiment, the intelligent physiological decision-making module is a three-layer serial decision-making structure:

[0087] The outer layer is the functional state decision layer, which determines whether the heart function and aortic vascular function of the current patient are in the optimal state according to the results of the heart function evaluation module and the vascular biomechanics evaluation module. If the deviation from the optimal state exceeds the set threshold, it makes adjustments to the working level of the artificial heart. The working level of the artificial heart includes the optimal working speed, optimal working torque, and optimal input power of the artificial heart;

[0088] The middle layer is the physiological state decision layer, which takes the working level of the artificial heart determined by the functional decision layer as input, calculates the unloading level of the artificial heart according to electromechanical signals such as the pressure difference at the inlet and outlet of the artificial heart, the output blood flow, and the input current level. The unloading level is measured by the BAI index. When abnormal physiological states such as ventricular suction (BAI > 100%), excessive unloading (BAI < 100% and BAI > 80%), or pulmonary congestion (BAI < 20%) occur, the control strategy of this layer responds in a timely manner and adjusts the current set speed of the artificial heart;

[0089] ​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​

[0101]

[0102] BAI – Unloading Level of Artificial Heart

[0103] u(k) — The current set rotational speed of the artificial heart.

[0104] The physiological state decision layer algorithm uses nonparametric model adaptive control theory to construct the control law, and takes the ventricular unloading level of the artificial heart as the control variable. When it is found that the actual ventricular unloading level deviates too much from the preset value, the working speed of the artificial heart will be adjusted.

[0105] Once the decision module determines the operating speed of the artificial heart based on the real-time working status of the patient and the artificial heart, it will send the operating speed to the drive module. The drive module will then adjust the stator magnetic field of the artificial heart to achieve speed adjustment of the response.

[0106] The intelligent physiological control strategy determines the optimal working state for promoting cardiac function recovery and maintaining normal vascular function by searching for extreme values ​​of cardiac function index and blood flow vortex index.

[0107] The intelligent physiological control strategy employs a non-parametric model adaptive control strategy to construct a physiological state decision algorithm, which adjusts the unloading level of the artificial heart accordingly.

[0108] The basic principles, main features, and advantages of the present invention have been described above. It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the invention can be implemented in other specific forms without departing from its spirit or essential characteristics. Therefore, the embodiments should be considered illustrative and non-limiting in all respects, and the scope of the invention is defined by the appended claims rather than the foregoing description. Thus, all variations falling within the meaning and scope of equivalents of the claims are intended to be included within the present invention. No reference numerals in the claims should be construed as limiting the scope of the claims.

[0109] Furthermore, it should be understood that although this specification describes embodiments, not every embodiment contains only one independent technical solution. This narrative style is merely for clarity. Those skilled in the art should consider the specification as a whole, and the technical solutions in each embodiment can also be appropriately combined to form other embodiments that can be understood by those skilled in the art.

Claims

1. An intelligent physiological control system for an artificial heart. The system includes an electromechanical physiological parameter detection module, a heart function evaluation module, a vascular biomechanics evaluation module, and an intelligent physiological decision-making module. It is characterized in that: The electromechanical physiological parameter detection module can collect and detect the electromechanical signals during the operation of the artificial heart and the physiological parameters of the patient; The heart function evaluation module evaluates the current heart function index of the patient according to the physiological parameters of the patient; The vascular biomechanics evaluation module calculates the blood flow swirl index according to the collected electromechanical signals; The intelligent physiological decision-making module can make decisions according to the changes in the heart function index and the blood flow swirl index, determine the optimal working level of the current artificial heart; determine the current set rotational speed value of the artificial heart according to the optimal working level of the current artificial heart; Subsequently, adjust the working current and rotor speed of the artificial heart according to the current set rotational speed value of the artificial heart; The physiological parameters of the patient include the patient's mean arterial pressure, cardiac cycle, electrocardiogram signal, and cardiac output data. Among them, the cardiac cycle signal of the patient is extracted from the patient's electrocardiogram signal, and its change over time is calculated; The change of mean arterial pressure over time is calculated using the mean arterial pressure signal and cardiac output data; The electromechanical signals include: the rotational speed of the artificial heart, the output blood flow, the pressure difference between the inlet and outlet of the artificial heart, the rotor vibration amplitude, and the input current. Among them, the spatial distribution law of the blood flow velocity in the blood vessel is calculated according to the rotational speed of the artificial heart, the output blood flow, the pressure difference between the inlet and outlet of the artificial heart, the rotor vibration amplitude, and the input current; the blood flow vorticity distribution is calculated according to the spatial distribution of the blood flow velocity, and then the blood flow swirl intensity in the blood vessel is calculated according to the blood flow velocity and the blood flow vorticity, which is characterized by the blood flow swirl index; The vascular biomechanics evaluation module calculates the blood flow swirl index according to the following formula: ； u - blood flow velocity —Blood flow vortex; t - time p - blood pressure —Blood density; —The turbulent viscosity of blood; LNH - blood flow swirl index; s - position coordinate in space; The intelligent physiological decision-making module is a three-layer serial decision-making structure: The outer layer is the functional state decision-making layer. It judges whether the heart function and aortic vascular function of the current patient are in the best state according to the results of the heart function evaluation module and the vascular biomechanics evaluation module. If it deviates from the best state by more than the set threshold, adjust the working level of the artificial heart. The working level of the artificial heart includes the optimal working rotational speed, the optimal working torque, and the optimal input power of the artificial heart; The middle layer is the physiological state decision-making layer. It takes the working level of the artificial heart determined by the functional decision-making layer as the input, calculates the unloading level of the artificial heart according to the electromechanical signals such as the pressure difference between the inlet and outlet of the artificial heart, the output blood flow, and the input current level. The unloading level is measured by the BAI index. When BAI > 100%, it indicates ventricular aspiration. When 80% < BAI < 100%, it indicates over-unloading. When BAI < 20%, it indicates pulmonary congestion. The control strategy of this layer makes a timely response and adjusts the current set rotational speed value of the artificial heart; The inner layer is the electromechanical state decision layer, which takes the desired rotational speed of the artificial heart determined by the functional state decision layer as the input signal. Based on the rotational speed of the artificial heart, the input current, and the rotor vibration amplitude signal, it constructs an actual state observer of the artificial heart. When the actual state deviates from the ideal state, the control strategy of this layer actively adjusts the input current and the rotor speed to ensure the stability and reliability of the operation of the artificial heart electromechanical system.

2. The artificial heart intelligent physiological control system according to claim 1, characterized in that: The cardiac function assessment module calculates the cardiac function index according to the following formula: ； t c —Heartbeat cycle; t — time MAP—Mean Arterial Pressure; BRS – Heart Function Index; —The cardiac cycle changes over time; —Changes in mean arterial pressure over time.

3. The artificial heart intelligent physiological control system according to claim 1, characterized in that: The functional state decision layer of the intelligent physiological decision module adjusts the working level of the artificial heart according to the following formula: ； —The tracking signal of the input signal; —Input signal; The time signal in a k-discrete system, that is, the k-th sampling time. —The derivative of the input signal; —The functional decision layer algorithm tracks the convergence speed variable; h—integration step size —The second derivative of the controlled object is used to describe the acceleration characteristics of the controlled object; —The core structure of the tracking differentiator, used to observe the higher-order derivatives of the controlled object.

4. The artificial heart intelligent physiological control system according to claim 2, characterized in that: The physiological state decision layer of the intelligent physiological decision module calculates the unloading level of the artificial heart and adjusts the current set rotation speed value of the artificial heart according to the following formula: ； —The level of unloading for artificial hearts; —The current set rotational speed of the artificial heart; —Power supply voltage for the artificial heart pump; —The current value flowing through the artificial heart pump; —At the speed of the artificial heart pump The efficiency of the artificial heart pump; —Instantaneous arterial blood pressure value; —Instantaneous arterial blood flow; —Step size parameter of the pseudo-partial derivative estimation algorithm; —Step size parameter of the adaptive control law; —The pseudo-partial derivative at time k — The measured value of BAI at time k; — The set value of BAI at time k; — Weight values ​​of the pseudo-partial derivative estimation algorithm; k-time signal.

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