Magnetic suspension total artificial heart and self-adaptive flow regulation and control method thereof

Abstract

The invention discloses a magnetic suspension total artificial heart and a self-adaptive flow regulation and control method thereof, and relates to the technical field of total artificial hearts.The method comprises the following regulation and control processes that multi-dimensional parameter information is sensed and collected in real time; carrying out physiological state evaluation and demand modeling; resolving by a self-adaptive control algorithm and adjusting the rotating speed; the magnetic suspension driving system dynamically executes the instruction; according to the invention, on the basis of the hardware architecture of the magnetic suspension full-artificial heart, the multi-parameter sensing module can collect pressure, flow and rotating speed signals in real time to realize accurate data input, and the control unit can construct a flow self-adaptive adjustment model based on physiological parameter changes, so that the flow self-adaptive adjustment can be realized. The rotating speeds of the left and right magnetic suspension blood pumps are dynamically adjusted through an adaptive algorithm, and the flow balance of systemic circulation and pulmonary circulation is maintained by dynamically, accurately and cooperatively adjusting the rotating speeds of the left and right blood pumps, so that the life quality and safety of a patient can be improved to the maximum extent.

Description

Technical Field

[0001] This invention relates to the field of total artificial heart technology, specifically to a magnetically levitated total artificial heart and its adaptive flow control method. Background Technology

[0002] Magnetic levitation total artificial heart is a revolutionary technology for treating end-stage heart failure. It achieves contactless levitation of the rotor inside the blood pump through magnetic levitation technology, which greatly reduces the risk of blood damage and thrombosis. The core of magnetic levitation technology is to use an electromagnetic field to stably levitate the impeller rotor inside the blood pump, completely avoiding mechanical bearings or blood lubrication, reducing blood cell damage. Blood flows through the pump body at high speed, reducing cell damage and coagulation risk, flushing the pump wall to prevent thrombosis, and solving the blood compatibility problem of traditional artificial hearts. At present, total artificial heart is mainly suitable for end-stage heart failure patients who cannot be saved by heart transplantation. Currently, in the process of flow regulation in a total artificial heart, the data acquisition and input process cannot fully and accurately collect pressure, flow, and speed signals, resulting in a single data structure and an inability to achieve accurate and effective data input. At the same time, the left and right blood pump components cannot maintain the radial and axial stable suspension of the rotors, and the speed of the left and right blood pumps cannot effectively maintain the flow balance between the systemic and pulmonary circulations. Summary of the Invention

[0003] This invention provides a magnetically levitated total artificial heart and its adaptive flow control method, which can effectively solve the problems mentioned in the background art. In the current flow control process of total artificial hearts, the data acquisition and input process cannot comprehensively and accurately collect pressure, flow and speed signals, resulting in a single data structure and the inability to achieve accurate and effective data input. At the same time, the left and right blood pump components cannot maintain the radial and axial stable suspension of the rotor, and the speed of the left and right blood pumps cannot effectively maintain the flow balance between systemic circulation and pulmonary circulation.

[0004] To achieve the above objectives, the present invention provides the following technical solution: an adaptive flow regulation method for a magnetically levitated total artificial heart, the artificial heart comprising left and right blood pump components, a magnetically levitated drive system, a control unit and a multi-parameter sensing module, based on the hardware architecture of the magnetically levitated total artificial heart, utilizing the multi-parameter sensing module to sense the physiological state in real time, and dynamically adjusting the rotation speed of the left and right magnetically levitated blood pumps through the adaptive algorithm of the control unit, so as to achieve a precise balance between systemic circulation and pulmonary circulation. The following control procedures are included: Step S1: Real-time sensing and collection of multi-dimensional parameter information; Step S2, Physiological state assessment and demand modeling; Step S3: Adaptive control algorithm calculation and speed adjustment; Step S4: The magnetic levitation drive system dynamically executes commands; Step S5: Continuous closed-loop feedback and safety monitoring.

[0005] According to the above technical solution, step S1 serves as the sensing basis for flow regulation. It provides accurate input for subsequent precise regulation by comprehensively acquiring multi-dimensional signals. The multi-dimensional parameter information includes pressure signals, flow signals, and speed signals. When acquiring pressure signals, the inlet and outlet pressures of the left and right blood pumps are collected in real time based on the high-precision pressure sensor in the sensing module. Simultaneously acquire the pressure waveforms at the inlet and outlet of the left and right blood pumps, and focus on extracting the systolic pressure, diastolic pressure, and mean pressure of each ventricle; When acquiring flow signals, flow acquisition devices are used to monitor the instantaneous output flow of the left and right blood pumps in real time. When acquiring the rotational speed signal, the position sensor in the magnetic levitation drive system provides real-time feedback on the rotor's rotational speed, as well as the rotor's minute radial and axial displacements and actual levitation position.

[0006] According to the above technical solution, in step S1, after acquiring the pressure, flow rate and speed signals, it is necessary to perform timestamp alignment and filter the acquired multidimensional signal parameters. At the same time, the acquired analog signals need to be processed by high-speed analog-to-digital conversion to convert analog quantities into digital quantities for processing by the control unit and to calculate physiological characteristic values.

[0007] According to the above technical solution, in step S2, based on the preprocessed multi-dimensional parameter data, the built-in algorithm inside the control unit is used to determine the current physiological needs. In the specific assessment and judgment process, it is necessary to initially construct a flow adaptive adjustment model and configure the ideal hemodynamic curves of the human body under different metabolic states within the model; The model uses venous return and peripheral vascular resistance as input variables, and the model output variables are the ideal target flow rates of the left and right blood pumps.

[0008] According to the above technical solution, in step S2, during state identification, it is necessary to analyze the filling status of the left and right ventricles. That is, when the inlet pressure decreases and the flow rate decreases, it indicates insufficient preload; when the outlet pressure increases and the flow rate is obstructed, it indicates increased afterload.

[0009] According to the above technical solution, in step S3, when adjusting the rotation speed, it is necessary to calculate the target flow rate and convert the physiological demand into a specific motor speed control command. This is mainly based on the currently identified physiological state and the model to calculate the ideal target flow rate of the left blood pump and the target flow rate of the right blood pump. When an imbalance in the flow rates of the left and right blood pumps is detected, the adaptive control algorithm automatically generates a correction term, making the target flow rate of the right blood pump equal to the sum of the target flow rate of the left blood pump and the correction term.

[0010] According to the above technical solution, in step S3, when generating the motor speed control command, the characteristic curves of the left and right blood pumps are used to map the target flow rate and the currently estimated backload to the target speed required by the left and right blood pumps, thereby generating independent speed commands for the left and right blood pumps respectively.

[0011] According to the above technical solution, step S4 converts the control command generated in step S3 into mechanical action while maintaining the rotor's non-contact stable suspension, specifically including magnetic levitation stability control and speed smooth adjustment. Among them, magnetic levitation stability control requires the magnetic levitation controller to ensure that the rotor remains in contactless and stable suspension in five degrees of freedom in the radial and axial directions before and during the adjustment of the rotational speed, while monitoring the rotor displacement in real time. The speed smoothing adjustment mainly adopts a ramp-up and down ramp strategy to avoid sudden speed changes that could cause excessive blood shear force and damage red blood cells, while avoiding hemodynamic shocks. This limits the speed change rate to within a safe threshold and drives the three-phase motor to change the frequency of the rotating magnetic field.

[0012] According to the above technical solution, step S5 is that after completing one adjustment cycle, the system enters the next monitoring cycle to form a continuous dynamic closed loop. Specifically, within a certain time window after the speed adjustment, the actual pressure, flow and speed data are collected again through the sensing module. Based on the data collected again, the error between the actual value and the target value is compared. If the error is within the allowable range, the current speed is maintained. If the error exceeds the preset threshold, the process needs to return to step S2.

[0013] According to the above technical solution, in step S5, when performing safety monitoring during the adjustment process, safety protection is mainly achieved based on the abnormal protection mechanism, which specifically includes air intake detection, imbalance alarm and fault self-test. The cavitation detection is determined when the inlet pressure drops sharply and the flow waveform is truncated; The imbalance alarm is triggered when the blood flow from the left and right blood pumps cannot be balanced for an extended period and exceeds a safe time limit. Fault self-check refers to the self-check performed by each sensing module. When one of the sensing signals is lost, or when the monitored value changes abnormally, the abnormal signal needs to be automatically removed.

[0014] According to the above technical solution, a magnetically levitated total artificial heart, and an artificial heart based on an adaptive flow control method for a magnetically levitated total artificial heart.

[0015] Compared with the prior art, the beneficial effects of the present invention are as follows: This invention comprises an artificial heart consisting of left and right blood pump components, a magnetic levitation drive system, a control unit, and a multi-parameter sensing module. The left and right blood pump components adopt a non-contact magnetic levitation support structure, utilizing magnetic levitation technology to minimize blood damage and achieve stable radial and axial levitation of the rotor. Based on the hardware architecture of the magnetic levitation full artificial heart, the multi-parameter sensing module is used to collect pressure, flow, and speed signals in real time to achieve precise data input and ensure the accuracy of subsequent adaptive flow control. The control unit can build an adaptive flow regulation model based on changes in physiological parameters, and dynamically adjust the rotation speed of the left and right magnetic levitation blood pumps through an adaptive algorithm. By dynamically and precisely coordinating the rotation speed of the left and right blood pumps, it can effectively maintain the flow balance between systemic and pulmonary circulation, thereby maximizing the improvement of patients' quality of life and safety. Attached Figure Description

[0016] The accompanying drawings are provided to further illustrate the invention and form part of the specification. They are used together with the embodiments of the invention to explain the invention and do not constitute a limitation thereof.

[0017] In the attached diagram: Figure 1 This is a flowchart of the adaptive flow control method of the present invention. Detailed Implementation

[0018] The preferred embodiments of the present invention will be described below with reference to the accompanying drawings. It should be understood that the preferred embodiments described herein are for illustration and explanation only and are not intended to limit the present invention.

[0019] Example: Figure 1 As shown, the present invention provides a technical solution, an adaptive flow control method for a magnetically levitated total artificial heart. The artificial heart includes left and right blood pump components, a magnetically levitated drive system, a control unit, and a multi-parameter sensing module. Based on the hardware architecture of the magnetically levitated total artificial heart, the multi-parameter sensing module is used to sense the physiological state in real time, and the rotation speed of the left and right magnetically levitated blood pumps is dynamically adjusted through the adaptive algorithm of the control unit to achieve a precise balance between systemic circulation and pulmonary circulation. The following control procedures are included: Step S1: Real-time sensing and collection of multi-dimensional parameter information; Step S2, Physiological state assessment and demand modeling; Step S3: Adaptive control algorithm calculation and speed adjustment; Step S4: The magnetic levitation drive system dynamically executes commands; Step S5: Continuous closed-loop feedback and safety monitoring.

[0020] Based on the above technical solution, step S1, as the sensing basis for flow regulation, provides accurate input for subsequent precise regulation by comprehensively acquiring multi-dimensional signals. The multi-dimensional parameter information includes pressure signal, flow signal and speed signal. When acquiring pressure signals, the inlet and outlet pressures of the left and right blood pumps are collected in real time based on the high-precision pressure sensor in the sensing module. The inlet pressure of the left and right blood pumps reflects the venous return volume, i.e., preload, while the outlet pressure of the left and right blood pumps reflects the arterial resistance, i.e., afterload. Simultaneously acquire the pressure waveforms at the inlet and outlet of the left and right blood pumps, and focus on extracting the systolic pressure, diastolic pressure, and mean pressure of each ventricle; When acquiring flow signals, a flow acquisition device is used to monitor the instantaneous output flow of the left and right blood pumps in real time. The flow acquisition device is selected from either an electromagnetic flow meter or an ultrasonic flow sensor. The left blood pump is located on the systemic circulation side and is used for systemic circulation, while the right blood pump is located on the pulmonary circulation side and is used for pulmonary circulation. When acquiring the rotational speed signal, the position sensor in the magnetic levitation drive system provides real-time feedback on the rotor's rotational speed, as well as the rotor's minute radial and axial displacements and actual levitation position, to determine the levitation stability.

[0021] Based on the above technical solution, in step S1, after acquiring pressure, flow and speed signals, it is necessary to perform timestamp alignment to ensure that the left and right heart data are comparable at the same time, and to filter the acquired multidimensional signal parameters. By filtering the original analog signal, abnormal spikes caused by blood turbulence and electromagnetic interference are eliminated. Specifically, high-frequency noise is removed by low-pass filtering. At the same time, the collected analog signals need to be processed by high-speed analog-to-digital conversion to convert analog quantities into digital quantities for processing by the control unit, and to calculate physiological characteristic values, including mean pressure, mean flow rate and pulsatility index.

[0022] Based on the above technical solution, in step S2, based on the preprocessed multi-dimensional parameter data, the built-in algorithm inside the control unit is used to determine the current physiological needs. In the specific assessment and judgment process, it is necessary to initially construct a flow adaptive regulation model. This model is mainly based on the Frank-Starling law of human physiology and exercise physiology curves. The Frank-Starling law states that the cardiac output increases with the increase of venous return. The model is configured with ideal hemodynamic curves of the human body under different metabolic states, specifically including resting state, exercise state and stress state. The model uses venous return and peripheral vascular resistance as input variables. Venous return is reflected by inlet pressure, and peripheral vascular resistance is estimated by the ratio of outlet pressure to flow rate. The model output variables are the ideal target flow rates of the left and right blood pumps.

[0023] Based on the above technical solution, in step S2, during state identification, it is necessary to analyze the filling status of the left and right ventricles. That is, when the inlet pressure decreases and the flow rate decreases, it indicates insufficient preload; when the outlet pressure increases and the flow rate is obstructed, it indicates increased afterload.

[0024] Based on the above technical solution, in step S3, when adjusting the speed, it is necessary to calculate the target flow rate and convert the physiological demand into a specific motor speed control command. In the specific calculation process, the ideal target flow rate of the left blood pump and the target flow rate of the right blood pump are calculated based on the currently identified physiological state and the model. When an imbalance in the flow rates of the left and right blood pumps is detected, the adaptive control algorithm automatically generates a correction term that makes the target flow rate of the right blood pump equal to the sum of the target flow rate of the left blood pump and the correction term. This introduces a balance correction coefficient to prioritize systemic circulation perfusion while preventing pulmonary congestion.

[0025] Based on the above technical solution, in step S3, when generating the motor speed control command, the characteristic curves of the left and right blood pumps are used. These characteristic curves are the head-flow-speed relationship curves. The target flow rate and the currently estimated backload are mapped to the target speeds required by the left and right blood pumps, thereby generating independent speed commands for the left and right blood pumps respectively.

[0026] Based on the above technical solution, in step S4, the control command generated in step S3 is converted into mechanical action while maintaining the rotor’s non-contact stable suspension, specifically including magnetic levitation stability control and speed smooth adjustment. Among them, magnetic levitation stability control ensures that the rotor remains in contactless and stable suspension in five degrees of freedom in the radial and axial directions before and during the adjustment of the rotational speed. At the same time, it monitors the rotor displacement in real time and immediately adjusts the electromagnetic coil current to counteract the disturbance force and prevent rotor collision and wear when the fluid excitation force changes due to the change of rotational speed. The smooth speed regulation mainly adopts a ramp-up and down ramp strategy to avoid excessive blood shear force caused by sudden speed changes, which could damage red blood cells. At the same time, it avoids hemodynamic shocks, keeps the speed change rate within a safe threshold, and drives the three-phase motor to change the frequency of the rotating magnetic field, so that the rotor can be accurately accelerated to the target speed and decelerated to the target speed.

[0027] Based on the above technical solution, step S5 is that after completing one adjustment cycle, the system enters the next monitoring cycle to form a continuous dynamic closed loop. Specifically, within a certain time window after the speed adjustment, that is, within 2-5 seconds, the actual pressure, flow and speed data are collected again through the sensor module. Based on the re-collected pressure, flow, and rotation speed data, the error between the actual value and the target value is compared. If the error is within the allowable range, the current rotation speed is maintained. However, if the error exceeds the preset threshold, it is necessary to return to step S2, reassess the physiological state, and fine-tune the model parameters for the next round of iterative adjustment.

[0028] Based on the above technical solution, in step S5, when conducting safety monitoring during the adjustment process, safety protection is mainly achieved based on the abnormal protection mechanism, which specifically includes air intake detection, imbalance alarm and fault self-test. The suction cavitation detection is determined when the inlet pressure drops suddenly and the flow waveform is truncated. At this time, the speed must be forcibly reduced immediately and an alarm response must be initiated. The imbalance alarm is triggered when the flow rates of the left and right blood pumps cannot be balanced for a long period of time and exceed the safe time limit. The alarm is then switched to the standby fixed speed mode to forcibly lock the speed difference between the left and right pumps. Fault self-check refers to the self-check performed by each sensing module. When one of the sensing signals is lost, or when the monitored value changes abnormally, the abnormal signal needs to be automatically removed. At the same time, the module needs to degrade its operation based on the remaining parameters to maintain basic life support.

[0029] According to the above technical solution, a magnetically levitated total artificial heart, and an artificial heart based on an adaptive flow control method for a magnetically levitated total artificial heart.

[0030] Finally, it should be noted that the above descriptions are merely preferred embodiments of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments or make equivalent substitutions for some of the technical features. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. An adaptive flow control method for a magnetically levitated total artificial heart, characterized in that: The artificial heart includes left and right blood pump components, a magnetic levitation drive system, a control unit, and a multi-parameter sensing module. Based on the hardware architecture of a magnetic levitation artificial heart, the multi-parameter sensing module is used to sense the physiological state in real time, and the speed of the left and right magnetic levitation blood pumps is dynamically adjusted through the adaptive algorithm of the control unit to achieve a precise balance between systemic circulation and pulmonary circulation. The following control procedures are included: Step S1: Real-time sensing and collection of multi-dimensional parameter information; Step S2, Physiological state assessment and demand modeling; Step S3: Adaptive control algorithm calculation and speed adjustment; Step S4: The magnetic levitation drive system dynamically executes commands; Step S5: Continuous closed-loop feedback and safety monitoring.

2. The adaptive flow control method for a magnetically levitated total artificial heart according to claim 1, characterized in that: Step S1 serves as the sensing basis for flow regulation. It comprehensively acquires multi-dimensional signals to provide accurate input for subsequent precise regulation. The multi-dimensional parameter information includes pressure signals, flow signals, and speed signals. When acquiring pressure signals, the inlet and outlet pressures of the left and right blood pumps are collected in real time based on the high-precision pressure sensor in the sensing module. Simultaneously acquire the pressure waveforms at the inlet and outlet of the left and right blood pumps, and focus on extracting the systolic pressure, diastolic pressure, and mean pressure of each ventricle; When acquiring flow signals, flow acquisition devices are used to monitor the instantaneous output flow of the left and right blood pumps in real time. When acquiring the rotational speed signal, the position sensor in the magnetic levitation drive system provides real-time feedback on the rotor's rotational speed, as well as the rotor's minute radial and axial displacements and actual levitation position.

3. The adaptive flow control method for a magnetically levitated total artificial heart according to claim 2, characterized in that: In step S1, after acquiring the pressure, flow rate, and speed signals, it is necessary to perform timestamp alignment and filter the acquired multidimensional signal parameters. At the same time, the acquired analog signals need to be processed by high-speed analog-to-digital conversion to convert analog quantities into digital quantities for processing by the control unit and to calculate physiological characteristic values.

4. The adaptive flow control method for a magnetically levitated total artificial heart according to claim 1, characterized in that: In step S2, based on the preprocessed multi-dimensional parameter data, the built-in algorithm inside the control unit is used to determine the current physiological needs. In the specific assessment and judgment process, it is necessary to initially construct a flow adaptive adjustment model and configure the ideal hemodynamic curves of the human body under different metabolic states within the model; The model uses venous return and peripheral vascular resistance as input variables, and the model output variables are the ideal target flow rates of the left and right blood pumps.

5. The adaptive flow control method for a magnetically levitated total artificial heart according to claim 4, characterized in that: In step S2, during state identification, it is necessary to analyze the filling status of the left and right ventricles. That is, when the inlet pressure decreases and the flow rate decreases, it indicates insufficient preload; when the outlet pressure increases and the flow rate is obstructed, it indicates increased afterload.

6. The adaptive flow control method for a magnetically levitated total artificial heart according to claim 1, characterized in that: In step S3, when adjusting the rotation speed, it is necessary to calculate the target flow rate and convert the physiological demand into a specific motor speed control command. This is mainly based on the currently identified physiological state and the model to calculate the ideal target flow rates for the left and right blood pumps. When an imbalance in the flow rates of the left and right blood pumps is detected, the adaptive control algorithm automatically generates a correction term, making the target flow rate of the right blood pump equal to the sum of the target flow rate of the left blood pump and the correction term.

7. The adaptive flow control method for a magnetically levitated total artificial heart according to claim 6, characterized in that: In step S3, when generating motor speed control commands, the characteristic curves of the left and right blood pumps are used to map the target flow rate and the currently estimated backload to the target speeds required by the left and right blood pumps, thereby generating independent speed commands for the left and right blood pumps respectively.

8. The adaptive flow control method for a magnetically levitated total artificial heart according to claim 6, characterized in that: Step S4 converts the control commands generated in step S3 into mechanical actions while maintaining the rotor’s non-contact stable suspension, specifically including magnetic levitation stability control and speed smooth adjustment. Among them, magnetic levitation stability control requires the magnetic levitation controller to ensure that the rotor remains in contactless and stable suspension in five degrees of freedom in the radial and axial directions before and during the adjustment of the rotational speed, while monitoring the rotor displacement in real time. The speed smoothing adjustment mainly adopts a ramp-up and down ramp strategy to avoid sudden speed changes that could cause excessive blood shear force and damage red blood cells, while avoiding hemodynamic shocks. This limits the speed change rate to within a safe threshold and drives the three-phase motor to change the frequency of the rotating magnetic field.

9. The adaptive flow control method for a magnetically levitated total artificial heart according to claim 4, characterized in that: Step S5 involves the system entering the next monitoring cycle after completing one adjustment cycle, forming a continuous dynamic closed loop. Specifically, within a certain time window after the speed adjustment, the actual pressure, flow rate, and speed data are collected again through the sensing module. Based on the data collected again, the error between the actual value and the target value is compared. If the error is within the allowable range, the current speed is maintained. If the error exceeds the preset threshold, the process needs to return to step S2.

10. The adaptive flow control method for a magnetically levitated total artificial heart according to claim 9, characterized in that: In step S5, when performing safety monitoring during the adjustment process, safety protection is mainly achieved based on the abnormal protection mechanism, which specifically includes air intake detection, imbalance alarm and fault self-check. The cavitation detection is determined when the inlet pressure drops sharply and the flow waveform is truncated; The imbalance alarm is triggered when the blood flow from the left and right blood pumps cannot be balanced for an extended period and exceeds a safe time limit. Fault self-check refers to the self-check performed by each sensing module. When one of the sensing signals is lost, or when the monitored value changes abnormally, the abnormal signal needs to be automatically removed.

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