Blood pump pressure information detection method, device and equipment and blood pump

Abstract

The invention discloses a blood pump pressure information detection method, device and equipment and a blood pump, and belongs to the technical field of artificial heart. The method comprises the steps that in the working process of a blood pump device assisting a target object, operation signal data of the blood pump device are acquired; obtaining at least one correction factor corresponding to the target object; and performing conversion processing based on the at least one correction factor and the operation signal data to obtain correction pressure data corresponding to the pump head. In the technical scheme provided by the embodiment of the invention, the correction factor capable of representing the offset error between the predicted pressure corresponding to the pump head and the actual pressure is introduced into the conversion processing of converting the blood pump operation signal into the pressure data at the pump head, so that the pump head pressure data which is more accurate and reliable and more conforms to the current target object is obtained; offset errors generated by factors such as target object individual differences and blood pump device individual differences are corrected.

Description

Technical Field

[0001] This application relates to the field of artificial heart technology, and in particular to a method, device, equipment and blood pump for detecting blood pump pressure information. Background Technology

[0002] Blood pump devices are used to provide mechanical circulatory support for patients. An interventional blood pump is a percutaneous implantation device. Its pump head is inserted percutaneously into the heart via a peripheral blood vessel. As the blades in the pump head rotate, they draw blood from the ventricles of the heart into the aorta, thus providing ventricular assist function. During operation, the user typically needs to monitor the pump's pressure data to determine the device's operational status and the patient's physiological condition.

[0003] In some related technologies, blood pump pressure is monitored using pressure sensors. For example, a pressure sensor is placed at the pump head of an interventional blood pump. However, the limited space at the pump head significantly restricts the size of the pressure sensor, resulting in a shorter lifespan for small sensors. Furthermore, installing a pressure sensor at the pump head is difficult and involves complex assembly, leading to higher costs for the blood pump device. Simultaneously, during blood pumping, the pressure sensor is in continuous contact with blood, further reducing its lifespan and making it prone to damage. Additionally, substances from the blood can easily accumulate on the sensor's surface, limiting pressure detection accuracy.

[0004] In other related technologies, the pump head of the interventional blood pump does not have a pressure sensor. Some of the blood pump's operating data is predicted based on a preset prediction model, such as a statistical curve model. These models are basically determined through hydraulic simulation experiments and may not match human hemodynamics. Furthermore, they do not take into account individual differences of the target object and individual differences of the blood pump device. The accuracy of data prediction is low, resulting in low reliability and safety of the equipment. Summary of the Invention

[0005] This application provides a method, apparatus, device, and blood pump for detecting blood pump pressure information, which can improve the accuracy of detecting blood pump pressure data.

[0006] According to one aspect of the embodiments of this application, a method for detecting blood pump pressure information is provided, the method comprising:

[0007] During the operation of the blood pump device assisting the target object, the operating signal data of the blood pump device is acquired, and the blood pump device includes a pump head;

[0008] At least one correction factor corresponding to the target object is obtained; wherein the correction factor characterizes the error between the predicted pressure and the actual pressure corresponding to the pump head; the correction factor is determined when the blood pump device is in a calibration operation state, the calibration operation state including one or more situations in which the actual pressure corresponding to the pump head can be determined, measured or estimated;

[0009] Based on the at least one correction factor and the operating signal data, the correction pressure data corresponding to the pump head is obtained through conversion processing.

[0010] In an exemplary embodiment, obtaining at least one correction factor corresponding to the target object includes:

[0011] During the calibration operation, a sample of the operating signal data is acquired;

[0012] The operating signal data samples are converted and processed to obtain the predicted pressure data samples corresponding to the pump head;

[0013] Identify feature points in the predicted pressure data sample that are associated with one or more of the aforementioned conditions;

[0014] The correction factor is determined based on the predicted pressure corresponding to the feature point and the actual pressure corresponding to one or more of the situations.

[0015] In an exemplary embodiment, the method further includes:

[0016] The pump speed of the blood pump device is controlled to enter the calibration operation state to meet the conditions for the occurrence of one or more of the above situations;

[0017] The step of obtaining at least one correction factor corresponding to the target object includes:

[0018] In the calibration operation state, the at least one calibration factor is determined or updated.

[0019] In an exemplary embodiment, controlling the pump speed of the blood pump device to enter the calibration operation state includes:

[0020] In response to the blood pump start command, the blood pump device is started, and the rotation speed of the blood pump device is controlled to increase to a first target rotation speed;

[0021] The blood pump device is controlled to operate based on the first target rotational speed;

[0022] The calibration operating state includes the state in which the blood pump device operates based on the first target rotational speed.

[0023] In an exemplary embodiment, controlling the pump speed of the blood pump device to enter the calibration operation state includes:

[0024] During the operation of the blood pump device, the target speed of the blood pump device is adjusted to the first target speed;

[0025] The blood pump device is controlled to operate based on the first target rotational speed;

[0026] The calibration operating state includes the state in which the blood pump device operates based on the first target rotational speed.

[0027] In an exemplary embodiment, adjusting the target rotation speed of the blood pump device to a first target rotation speed during operation includes:

[0028] If a calibration command is received during the operation of the blood pump device, the calibration cycle is reached, or the target parameter in the blood pump device is detected to be abnormal, the target speed of the blood pump device will be adjusted to the first target speed.

[0029] And / or, during the operation of the blood pump device, a calibration prompt message is issued; in response to a confirmation message for the calibration prompt message, the target speed of the blood pump device is adjusted to the first target speed.

[0030] In an exemplary embodiment, the step of issuing a calibration prompt message during operation of the blood pump device includes:

[0031] The calibration prompt message is issued when the blood pump device reaches the calibration cycle or when the target parameter in the blood pump device is detected to be abnormal.

[0032] The step of adjusting the target speed of the blood pump device to the first target speed in response to the confirmation information for the calibration prompt includes:

[0033] In response to a confirmation operation of the calibration prompt information, the target speed of the blood pump device is adjusted to the first target speed.

[0034] In an exemplary embodiment, after determining or updating the at least one correction factor in the correction operation state, the method further includes:

[0035] The target speed of the blood pump device is adjusted from the first target speed to the second target speed, where the second target speed refers to the target speed set based on the control operation.

[0036] The blood pump device is operated based on the second target rotational speed.

[0037] In an exemplary embodiment, the step of performing conversion processing based on the at least one correction factor and the operating signal data to obtain the correction pressure data corresponding to the pump head includes:

[0038] The operating signal data is converted and processed to obtain the predicted pressure data corresponding to the pump head;

[0039] The predicted pressure data is corrected based on the at least one correction factor to obtain the corrected pressure data.

[0040] In an exemplary embodiment, the step of correcting the predicted pressure data based on the at least one correction factor to obtain the corrected pressure data includes:

[0041] The predicted pressure data is corrected by applying the at least one correction factor to correct the offset error.

[0042] In an exemplary embodiment, the step of performing conversion processing based on the at least one correction factor and the operating signal data to obtain the correction pressure data corresponding to the pump head includes:

[0043] Based on the at least one correction factor, the operating signal data is corrected to obtain corrected operating signal data;

[0044] The operating signal correction data is converted and processed to obtain the correction pressure data corresponding to the pump head.

[0045] In an exemplary embodiment, the step of correcting the operating signal data based on the at least one correction factor to obtain corrected operating signal data includes:

[0046] The offset error is corrected by applying the at least one correction factor to the operating signal data to obtain the corrected operating signal data.

[0047] In an exemplary embodiment, the method further includes:

[0048] A pump head pressure prediction model is obtained, which characterizes the conversion relationship between the operating signal of the blood pump device and the pump head pressure.

[0049] The conversion processing based on the at least one correction factor and the operating signal data to obtain the corrected pressure data corresponding to the pump head includes:

[0050] The operating signal data is input into the pump head pressure prediction model for conversion processing, and the predicted pressure data corresponding to the pump head is output; the predicted pressure data is corrected based on the at least one correction factor to obtain the corrected pressure data;

[0051] Alternatively, the operating signal data can be corrected based on the at least one correction factor to obtain corrected operating signal data; the corrected operating signal data can be input into the pump head pressure prediction model for conversion processing to output the corrected pressure data.

[0052] Alternatively, based on the at least one correction factor, the pump head pressure prediction model is corrected to obtain a corrected pump head pressure prediction model; the operating signal data is input into the corrected pump head pressure prediction model for conversion processing, and the corrected pressure data is output.

[0053] In an exemplary embodiment, the pump head pressure prediction model is obtained by adjusting the parameters of the original pump head pressure prediction model based on hydraulic test results.

[0054] In an exemplary embodiment, the acquisition of the pump head pressure prediction model includes:

[0055] Acquire operational signal test data samples and pump head pressure detection data samples corresponding to the operational signal test data samples;

[0056] Based on the operating signal test data sample and the pump head pressure detection data sample, the pump head pressure prediction model is generated;

[0057] The pump head pressure prediction model includes at least one of the following:

[0058] Linear relational models, non-linear relational models, lookup tables, and machine learning models.

[0059] In an exemplary embodiment, acquiring the operating signal data of the blood pump device includes:

[0060] Obtain the raw data of the running signals;

[0061] The raw data is subjected to signal processing to obtain the running signal data; wherein the signal processing method includes at least one of the following:

[0062] Based on low-pass filter filtering;

[0063] Based on bandpass filter filtering;

[0064] Determine the average value of the operating signal data over a fixed time period;

[0065] Determine the average value of the operating signal data over the target number of heartbeat cycles;

[0066] Determine the root mean square value of the operating signal data within a fixed time period;

[0067] Determine the root mean square value of the operating signal data over the target number of heartbeat cycles;

[0068] Determine the basic values ​​of the operating signal data within a fixed time period;

[0069] Determine the basic value of the operating signal data over the target number of heartbeat cycles.

[0070] In an exemplary embodiment, the method further includes at least one of the following steps:

[0071] Determine the average net pressure corresponding to the corrected pressure data over a fixed time period;

[0072] Determine the average net pressure corresponding to the corrected pressure data over the target number of heartbeat cycles;

[0073] Determine the root mean square net pressure value corresponding to the corrected pressure data over a fixed time period;

[0074] Determine the root mean square net pressure value of the corrected pressure data for the target number of heartbeat cycles;

[0075] Determine the amplitude of the net pressure fundamental frequency component corresponding to the corrected pressure data over a fixed time period;

[0076] Determine the amplitude of the net pressure fundamental frequency component corresponding to the target number of heartbeat cycles of the corrected pressure data;

[0077] Determine the net pressure waveform spectrum corresponding to the corrected pressure data.

[0078] In an exemplary embodiment, the method further includes at least one of the following steps:

[0079] Display the calibration pressure data;

[0080] An alarm message is triggered based on the corrected pressure data;

[0081] Based on the corrected pressure data and aortic pressure data, left ventricular pressure data is determined, wherein the aortic pressure data is obtained from the detection module corresponding to the blood pump device;

[0082] The calibration pressure data is converted to obtain the pump flow indication data corresponding to the blood pump device;

[0083] Based on the corrected pressure data, pump position indication information is determined.

[0084] In an exemplary embodiment, the at least one correction factor includes at least one of the following:

[0085] The operating signal correction factor, the conversion relationship correction factor, and the pressure data correction factor are defined as follows: the operating signal correction factor represents the correction factor corresponding to the operating signal data; the conversion relationship correction factor represents the correction factor corresponding to the conversion relationship between the operating signal data and the predicted pressure data; the predicted pressure data is the predicted pressure obtained by converting the operating signal data based on the conversion relationship; and the pressure data correction factor represents the correction factor corresponding to the predicted pressure data.

[0086] The at least one correction factor includes at least one of the following:

[0087] Offset value, scaling factor.

[0088] In an exemplary embodiment, the pressure data correction factor includes at least one of a fixed pressure offset value and a speed-related pressure offset value, wherein the pressure offset value characterizes the offset error between the predicted pressure and the actual pressure corresponding to the pump head;

[0089] The operating signal correction factor includes at least one of a fixed current offset value and a speed-related current offset value;

[0090] The scaling factor includes at least one of a fixed scaling factor and a speed-related scaling factor.

[0091] In an exemplary embodiment, the operating signal data includes rotational speed signal data corresponding to the blood pump device, and the rotational speed signal data includes at least one of motor rotational speed data, impeller rotational speed data, rotational speed error data, and coupled rotational speed difference data;

[0092] The speed error data refers to the error data between the target speed and the actual speed, and the coupled speed difference data refers to the speed difference data between the coupled drive components in the blood pump device.

[0093] In an exemplary embodiment, the operating signal data includes torque sensing data.

[0094] In an exemplary embodiment, the operating signal data includes current data, which includes at least one of the following:

[0095] Motor controller current data, motor current.

[0096] In an exemplary embodiment, the motor controller current data includes at least one of the following:

[0097] The net output current of the motor controller;

[0098] The proportional term current corresponding to the PID control module; the motor controller includes a PID control module.

[0099] Current data determined based on the proportional term current and derivative term current corresponding to the PID control module;

[0100] The current data is determined based on the proportional term current and integral term current corresponding to the PID control module.

[0101] In an exemplary embodiment, the motor current includes at least one of the following:

[0102] The current in at least one motor winding of the motor;

[0103] The average current corresponding to at least two motor windings;

[0104] The orthogonal axis current is determined based on the motor winding current, wherein the motor winding current is obtained based on the motor position transformation.

[0105] In an exemplary embodiment, the corrected pressure data includes corrected pump head net pressure data, and the one or more cases include at least one of the following:

[0106] The opening of the aortic valve during a cardiac cycle;

[0107] The pump head net pressure is based on measurements from a net pressure sensor.

[0108] The inlet and outlet pressures of the pump head are based on measurements from pressure sensors;

[0109] One of the pump head's inlet pressure and outlet pressure is measured by a sensor, while the other is determined or estimated based on physiological effects.

[0110] In an exemplary embodiment, the method further includes:

[0111] Obtain the blood viscosity data of the target object;

[0112] The conversion processing based on the at least one correction factor and the operating signal data to obtain the corrected pressure data corresponding to the pump head includes:

[0113] Based on the at least one correction factor, the blood viscosity data, and the operating signal data, the correction pressure data corresponding to the pump head is obtained through conversion processing.

[0114] In an exemplary embodiment, the step of performing conversion processing based on the at least one correction factor, the blood viscosity data, and the operating signal data to obtain the correction pressure data corresponding to the pump head includes:

[0115] Based on the blood viscosity data, the model parameters of the pump head pressure prediction model are adjusted to obtain a pump head pressure prediction model that matches the current blood viscosity. The pump head pressure prediction model represents the conversion relationship between the operating signal of the blood pump device and the pump head pressure.

[0116] Based on the adjusted pump head pressure prediction model, at least one correction factor and the operating signal data are converted to obtain the above-mentioned corrected pressure data.

[0117] In an exemplary embodiment, the blood pump device includes a pressure sensor, and the operating modes corresponding to the pressure sensor include an operating mode and a deactivation mode;

[0118] In the shutdown mode, the step of performing conversion processing based on the at least one correction factor and the operating signal data to obtain the correction pressure data corresponding to the pump head is executed.

[0119] According to one aspect of the embodiments of this application, a blood pump pressure information detection device is provided, the device comprising:

[0120] The data acquisition module is used to acquire the operating signal data of the blood pump device during the operation of the blood pump device assisting the target object. The blood pump device includes a pump head.

[0121] A correction factor acquisition module is used to acquire at least one correction factor corresponding to the target object; wherein the correction factor characterizes the error between the predicted pressure and the actual pressure corresponding to the pump head; the correction factor is determined when the blood pump device is in a calibration operation state, the calibration operation state including one or more situations in which the actual pressure corresponding to the pump head can be determined, measured or estimated;

[0122] The pressure conversion and correction module is used to perform conversion processing based on the at least one correction factor and the operating signal data to obtain the corrected pressure data corresponding to the pump head.

[0123] According to one aspect of the embodiments of this application, an electronic device is provided, the electronic device including a processor and a memory, the memory storing at least one instruction, at least one program, code set or instruction set, the at least one instruction, the at least one program, the code set or instruction set being loaded and executed by the processor to implement the above-described blood pump pressure information detection method.

[0124] According to one aspect of the embodiments of this application, a blood pump is provided, the blood pump including a processor and a memory, the memory storing at least one instruction, at least one program, code set or instruction set, the at least one instruction, the at least one program, the code set or instruction set being loaded and executed by the processor to implement the blood pump pressure information detection method as described in any one of claims 1 to 29.

[0125] According to one aspect of the embodiments of this application, a computer-readable storage medium is provided, wherein the storage medium stores at least one instruction, at least one program, code set or instruction set, wherein the at least one instruction, the at least one program, the code set or instruction set is loaded and executed by a processor to implement the above-described blood pump pressure information detection method.

[0126] According to one aspect of the embodiments of this application, a computer program product is provided, the computer program product including computer instructions stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium, and the processor executes the computer instructions, causing the computer device to perform the above-described blood pump pressure information detection method.

[0127] The technical solution provided in this application can bring the following beneficial effects:

[0128] During the calibration operation of the blood pump device, one or more situations may occur where the actual pressure corresponding to the pump head can be determined, measured, or estimated. Therefore, during the calibration operation, a correction factor that can characterize the deviation error between the predicted pressure and the actual pressure corresponding to the pump head is determined and used as input data. This correction factor is then introduced into the conversion process that converts the blood pump operation signal into pressure data at the pump head. This corrects the deviation error caused by factors such as individual differences of the target object and individual differences of the blood pump device. Thus, under the current operating conditions of the blood pump device, more accurate, reliable, and more suitable pump head pressure data for the current target object can be obtained through conversion processing based on the correction factor.

[0129] Furthermore, the technical solution provided in this application is applicable not only to blood pump devices without relevant sensors at the pump head, but also to blood pump devices with relevant sensors at the pump head. In the case of failure of the relevant sensors or invalid detection data in the latter, the above method can still be used to predict the pressure at the pump head. Attached Figure Description

[0130] To more clearly illustrate the technical solutions in the embodiments of this application, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0131] Figure 1 This is a schematic diagram of the structure of a blood pump device provided in an embodiment of this application;

[0132] Figure 2 An exemplary schematic diagram shows a structure connecting an interventional pump to a fluid pipeline;

[0133] Figure 3 This is a flowchart of a blood pump pressure information detection method provided in one embodiment of this application;

[0134] Figure 4 An example is shown: a graph of actual cardiac pressure under normal aortic valve opening and closing conditions;

[0135] Figure 5 An exemplary schematic diagram of the pump head pressure prediction curve under normal aortic valve opening and closing conditions is shown.

[0136] Figure 6 An exemplary diagram illustrates the application of a net pressure correction factor to correct the offset error of the pump head net pressure prediction data curve.

[0137] Figure 7 This is a flowchart of a blood pump control method provided in one embodiment of this application;

[0138] Figure 8 This is a block diagram of a blood pump pressure information detection device provided in one embodiment of this application;

[0139] Figure 9 This is a block diagram of a blood pump control device provided in one embodiment of this application. Detailed Implementation

[0140] To make the objectives, technical solutions, and advantages of this application clearer, the embodiments of this application will be further described in detail below with reference to the accompanying drawings. Exemplary embodiments will be described in detail here, examples of which are illustrated in the accompanying drawings. When the following description refers to the drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this application as detailed in the appended claims.

[0141] The terminology used in this disclosure is for the purpose of describing particular embodiments only and is not intended to be limiting of the disclosure. The singular forms “a,” “the,” and “the” as used in this disclosure and the appended claims are also intended to include the plural forms unless the context clearly indicates otherwise. It should also be understood that the term “and / or” as used herein refers to and includes any and all possible combinations of one or more of the associated listed items.

[0142] It should be understood that although the terms first, second, third, etc., may be used in this disclosure to describe various information, such information should not be limited to these terms. These terms are only used to distinguish information of the same type from one another.

[0143] Before introducing the method embodiments provided in this application, a brief introduction will be given to the relevant technical background, related terms or nouns that may be involved in the method embodiments of this application, so as to facilitate the understanding of those skilled in the art.

[0144] A blood pump device is a circulatory auxiliary device that replaces the function of the ventricles, including but not limited to external blood pump devices, interventional blood pump devices, and implantable blood pump devices.

[0145] An interventional blood pump device refers to a catheter-based pump used in medical settings to assist the heart in providing blood circulation. An interventional blood pump device includes an interventional blood pump (or simply interventional pump) and a control device used in conjunction with it, suitable for providing temporary ventricular circulation assistance during relevant surgeries. Optionally, the interventional blood pump is a cardiac pump inserted into a living organism. Optionally, some or all components of the interventional blood pump are inserted into a living organism. In operation, the drive device in the control device drives the interventional pump to pump blood from the ventricles into the aorta, thereby assisting the heart's pumping function and reducing the burden on the heart.

[0146] Figure 1 This is a schematic diagram of a blood pump device provided in an embodiment of this application. See also... Figure 1 As shown, the blood pump device is an interventional blood pump device, including an interventional pump 10 and a control device 20, which are detachably connected to the interventional pump 10. The interventional pump 10 is a consumable.

[0147] The control device 20 includes, but is not limited to, a console 21, a drive motor 22, and a flushing device 23. The console 21 is used at least to respond to human-machine interface operations and system control operations, allowing operators to monitor system status and patient physiological data, and adjust the speed of the blood pump 1 according to the patient's needs to provide different levels of circulatory assistance, thereby temporarily maintaining blood circulation to the patient's vital organs and relieving the burden on the heart. The drive motor 22 is used at least to drive the interventional pump 10.

[0148] The interventional pump 10 includes a drive catheter handle 11, a drive catheter 12, a pump head 13, and a protective end 14. The pump head 13 includes, but is not limited to, an impeller, a support, and a membrane.

[0149] The interventional pump 10 can be percutaneously inserted into the heart through peripheral blood vessels. The pump head 13 is placed between the left ventricle and the aorta. The blood inlet of the pump head 13 is placed into the left ventricle, and the blood outlet of the pump head is placed into the aorta, thereby pumping blood from the left ventricle into the aorta to achieve ventricular assist function.

[0150] Since the interventional pump 10 needs to be inserted into the human body, it needs to be pre-charged before use and kept flushed during use to prevent air from entering the body through the gaps inside the interventional pump 10 and to prevent blood from stagnating in the gaps inside the interventional pump 10 and forming thrombi. Therefore, the interventional pump 10 can also be connected to a flushing line. The flushing device 23 is used to drive the flushing fluid in the flushing line to pre-charge, vent, and flush the gaps inside the interventional pump 10, thereby preventing blood from entering the drive conduit 12 and forming thrombi, and preventing air from entering the target body through the gaps inside the interventional pump and forming air embolisms. The flushing device 23 may include a peristaltic pump, which drives and squeezes the pump tube in the flushing line to pump the flushing fluid into the interventional pump 10, thereby preventing air bubbles from entering the drive conduit 12 of the interventional pump 10.

[0151] Optionally, the interventional pump system can monitor the blood pressure of the target subject. The interventional pump has an arterial pressure measurement channel that remains connected to a blood vessel. An arterial pressure sensor is installed in the arterial pressure measurement channel; when the channel is connected to the blood vessel fluid, the sensor can detect the arterial pressure of the target subject. Therefore, the interventional pump 10 can also be connected to an arterial pressure measurement line. The arterial pressure measurement line has a periodically openable flushing valve. Pressure is applied to the fluid bag connected to the arterial pressure measurement line via a pressure bag, which can also drive fluid to flush the arterial pressure measurement pathway, preventing thrombosis.

[0152] As an example, see Figure 2 As shown, Figure 2 An exemplary schematic diagram of an interventional pump connected to a fluid line is shown. The fluid line includes a flushing line and an arterial pressure monitoring line 40. The flushing line includes an infusion line 31, a circulation inlet line 32, and a circulation outlet line 33. The infusion line 31 can be driven and squeezed by the infusion pump 231 in the flushing device 23, and the circulation inlet line 32 can be driven and squeezed by the circulation pump 232 in the flushing device.

[0153] After the drive catheter handle 11 is connected to the flushing pipeline, a flushing flow path is formed. Specifically, the flushing fluid inlet 111 of the drive catheter handle 11 is connected to the circulation inlet pipe 32 of the flushing pipeline, the flushing fluid outlet 112 of the drive catheter handle 11 is connected to the circulation outlet pipe 33 of the flushing pipeline, and the infusion pipe 31 of the flushing pipeline is connected to the fluid bag, forming the flushing flow path of the intervention pump 10. The infusion pump 231 drives the pump tube on the infusion pipe 31 to pump the flushing fluid in the fluid bag to the circulation inlet pipe 32, thereby driving the flushing fluid to enter the drive catheter handle 11 through the flushing fluid inlet 111. After the flushing fluid enters the drive catheter handle 11, part of it enters the drive catheter 12 through the flushing fluid chamber and is discharged to the human body from the pump head 13; the other part enters the coupling cooling chamber and flows back into the flushing pipeline from the flushing fluid outlet 112. The circulating pump 232 is used to drive the flushing fluid to circulate between the circulating inlet pipe 32, the drive guide handle 11, and the circulating outlet pipe 33, thereby cooling the flushing fluid and preventing the high temperature generated by the coupling rotation between the drive motor 22 and the intervention pump 10 from causing the flushing fluid to reach a high temperature. At the same time, the circulating flushing fluid has a cooling effect on the coupled rotor.

[0154] After the drive catheter handle 11 is connected to the arterial pressure measurement tubing 40, an arterial pressure measurement flow path is formed. Specifically, the pressure measurement inlet 113 of the drive catheter handle 11 is connected to the arterial pressure measurement tubing 40, and the pressure measurement outlet 114 of the drive catheter handle 11 is connected to the pressure measurement interface 51 of the interventional sheath 50. The interventional sheath 50, after being percutaneously inserted into the blood vessel, provides a pathway for the interventional pump 10 to be placed into the heart, and the interventional sheath 50 remains in the target blood vessel until the interventional pump 10 is removed. The fluid in the fluid bag connected to the arterial pressure measurement tubing 40 fills the entire arterial pressure measurement channel in the arterial pressure measurement tubing 40 and the interventional pump 10, and connects to the gap 53 between the interventional sheath 50 and the drive catheter 12, thereby maintaining communication with the blood in the blood vessel. Thus, the arterial pressure sensor 115 in the interventional pump can detect the arterial pressure of the target. The aforementioned arterial pressure sensor 115 is located outside the target body.

[0155] During the operation of the above-mentioned blood pump device, blood pump pressure is an important clinical reference data indicator. In order to solve the technical problems mentioned in the background section, this application provides a method for detecting blood pump pressure information.

[0156] Please refer to Figure 3 The diagram illustrates a flowchart of a blood pump pressure information detection method according to an embodiment of this application. This method can be applied to electronic devices, which are those capable of data calculation and processing. For example, the executing entity for each step could be... Figure 1 The illustrated blood pump device includes electronic equipment such as the control console 21 and the flushing device 23. The method may include the following steps (310-330).

[0157] Step 310: During the operation of the blood pump device assisting the target object, acquire the operating signal data of the blood pump device.

[0158] The aforementioned blood pump device includes a pump head.

[0159] Step 320: Obtain at least one correction factor corresponding to the target object.

[0160] The correction factor characterizes the error between the predicted pressure and the actual pressure corresponding to the pump head.

[0161] Optionally, the correction factor is determined when the blood pump device is in calibrated operating condition. The calibrated operating condition includes one or more scenarios where the actual pressure corresponding to the pump head can be determined, measured, or estimated.

[0162] Step 330: Based on at least one correction factor and the operating signal data, perform conversion processing to obtain the correction pressure data corresponding to the pump head.

[0163] The aforementioned blood pump device begins operation after its pump head is percutaneously inserted into the heart. The drive motor of the blood pump device rotates the impeller, pumping blood from the ventricles to the aorta. During the operation of the blood pump device, the periodic beating of the heart affects the pressure corresponding to the pump head. These pressure changes also cause changes in the relevant operating signals within the blood pump device. Therefore, historical data can be selected as samples to determine the conversion relationship between changes in operating signals during the cardiac cycle and changes in pressure at the pump head, thus realizing the conversion of blood pump device operating signal data to pressure data at the pump head.

[0164] The aforementioned operating signal data may be detection data of one or more signal parameters detectable from the blood pump device. The aforementioned operating signal data includes, but is not limited to, at least one of the following signal parameter data: rotational speed signal data, torque sensing data, and current data corresponding to the blood pump device.

[0165] Optionally, the aforementioned speed signal data includes, but is not limited to, at least one of motor speed data, impeller speed data, speed error data, and coupled speed difference data; wherein, speed error data refers to the error data between the target speed and the actual speed, and coupled speed difference data refers to the speed difference data between the coupled drive components in the blood pump device.

[0166] Optionally, the current data includes, but is not limited to, at least one of the following: motor controller current data, motor current.

[0167] Further optionally, the motor controller current data includes at least one of the following:

[0168] The net output current of the motor controller;

[0169] The proportional term current corresponding to the PID control module; the motor controller includes a PID control module.

[0170] Current data determined based on the proportional term current and derivative term current corresponding to the PID control module;

[0171] The current data is determined based on the proportional and integral term currents corresponding to the PID control module.

[0172] Further optionally, the motor current includes at least one of the following:

[0173] The current in at least one motor winding of the motor;

[0174] The average current corresponding to at least two motor windings;

[0175] The orthogonal axis current is determined based on the motor winding current, where the motor winding current is obtained based on the motor position transformation.

[0176] In an exemplary embodiment, the aforementioned operating signal data may be data that has undergone signal processing of the blood pump device's operating signals to reduce the influence of noise in the original signal data. The electronic equipment of the blood pump device can acquire the original operating signal data and perform signal processing on the original data to obtain the operating signal data.

[0177] The signal processing methods include, but are not limited to, at least one of the following:

[0178] The filtering process is based on a low-pass filter, in which a low-pass filter is used to reduce the impact of high-frequency signal noise.

[0179] The filtering process is based on bandpass filters, which are used to reduce the influence of high-frequency and low-frequency signal noise and further minimize the offset error components.

[0180] Determine the average value of the operating signal data over a fixed time period;

[0181] Determine the average value of the operating signal data over the target number of heartbeat cycles;

[0182] Determine the root mean square value of the operating signal data within a fixed time period;

[0183] Determine the root mean square value of the operating signal data over the target number of heartbeat cycles;

[0184] Determine the basic values ​​of the operating signal data within a fixed time period;

[0185] Determine the basic values ​​of the operating signal data within the target number of heartbeat cycles.

[0186] The pressures at the pump head mentioned above include, but are not limited to, pump head inlet pressure, left ventricular pressure, pump head outlet pressure, aortic pressure, and the net pressure (pressure difference) between the pump head outlet and inlet. Accordingly, the corrected pressure data determined in step 330 includes, but is not limited to, the following corrected data: pump head inlet pressure data, left ventricular pressure data, pump head outlet pressure data, aortic pressure data, and the net pressure data between the pump head outlet and inlet (hereinafter referred to as pump head net pressure data).

[0187] The above lists some convertible operating signal data and pump head pressure data. Those skilled in the art can select appropriate operating signal data as input data for conversion processing and appropriate pressure data as target prediction data based on actual conditions, such as blood pump type and blood pump sensor type. This application does not limit this.

[0188] However, the above conversion relationship is based on historical data samples and does not consider the differences between the new target object and operating conditions and the historical samples. On the one hand, most historical data samples are also based on hydraulic tests and animal experiments, which differ from human hemodynamics. In addition, there are differences in hemodynamics among individual target objects and hydraulic performance among individual blood pump devices. This will lead to a large offset error term when directly predicting the pressure at the pump head based on the above conversion relationship. On the other hand, if the blood pump device is an interventional blood pump with a large number of variable mechanical load sources, such as bearings and flexible mechanical transmission systems in the blood pump device, directly predicting the pressure at the pump head using the above conversion relationship usually results in significant errors. For example, the bearing friction load may change with the bearing temperature, or the load of the flexible mechanical transmission system may change with its bending degree. In interventional blood pumps with flexible mechanical transmission systems, the drive motor is typically externally mounted on the target object and connected to the proximal end of a flexible drive shaft. The distal end of the flexible drive shaft is connected to the pump head. The drive motor drives the flexible drive shaft to rotate, which in turn drives the impeller in the pump head to rotate. When the flexible drive shaft rotates in the catheter, it will rub against the inner wall of the catheter due to the bending of the catheter. Therefore, the mechanical load of the flexible mechanical transmission system is variable and varies with the degree of bending.

[0189] The above errors will cause the pressure data at the pump head to be offset based directly on the above conversion relationship, which will ultimately lead to low accuracy and reliability of pressure data detection. Therefore, it is necessary to correct this offset error in order to provide accurate pressure data at the pump head.

[0190] After discovering the above-mentioned problems and identifying their causes, the inventors of this application also found that the aforementioned error is constant under certain operating conditions, and studied a method to correct this offset error to calibrate the pressure data at the pump head, namely the method described above. Figure 3 The method shown.

[0191] Specifically, determining the aforementioned offset error requires specific pressure data as a reference. This means that certain data points in the pressure data waveform need to be related to certain specific values, such as the actual pressure corresponding to that point. These values ​​can be known or estimated from other measurement methods or physiological considerations of the target object. The aforementioned other measurement methods or physiological considerations of the target object can serve as one or more cases for determining the aforementioned at least one correction factor. Therefore, under one or more of the aforementioned cases, the actual pressure corresponding to the pump head can be determined, measured, or estimated.

[0192] The above one or more situations include, but are not limited to, at least one of the following situations:

[0193] The opening status of the aortic valve during the cardiac cycle; the net pressure of the pump head based on the measurement of the net pressure sensor; the inlet and outlet pressures of the pump head based on the measurement of the pressure sensor; the situation where one of the inlet and outlet pressures of the pump head is measured by a sensor, and the other is determined or estimated based on physiological effects.

[0194] In one or more of the above-described cases, the actual net pressure corresponding to the pump head can be determined, measured, or estimated. Accordingly, the corrected pressure data below includes the corrected net pressure data for the pump head. The following explanation addresses the cases listed above.

[0195] The aortic valve opening during a cardiac cycle can be applied to blood pump devices where no pressure sensor is located at the pump head. In some cases, the pump head is placed between the left ventricle and aorta of the target patient. It is known that the aortic valve opens at a specific point during a cardiac cycle, and therefore, the net pump pressure at that point has the physiological value of the net pressure when blood passes through the open aortic valve. By analyzing a portion of the pressure data waveform, such as partial pressure data over several cardiac cycles, and matching the predicted pressure at that point, determined based on the aforementioned conversion relationship, with the aforementioned physiological value of the actual net pressure, at least one correction factor characterizing the aforementioned offset error can be determined with sufficient accuracy. In this case, accurate pump head pressure data can be obtained without a sensor at the pump head.

[0196] The measurement of the pump head net pressure based on a net pressure sensor, and the measurement of the pump head inlet and outlet pressures based on pressure sensors, can be applied, but is not limited to, blood pump devices with relevant pressure sensors installed within the blood pump, or applications where additional pressure detection devices (such as patient monitors) are connected to the target object. This can be used to correct pressure data estimates (such as net pressure estimates) from operating signal data (such as speed). A net pressure (differential pressure) sensor can be installed at the pump head of the blood pump device, or pressure sensors can be installed at the inlet and outlet of the pump head respectively. Therefore, with the aforementioned net pressure sensor, or with the pressure sensors at the pump head inlet and outlet operating normally, the corresponding actual net pressure at the pump head, or the inlet and outlet pressures of the pump head, can be obtained. Since the aforementioned pressures are directly detected by sensors, the actual pressures (inlet pressure, outlet pressure, and net pressure between the outlet and inlet) can be determined. Therefore, the actual pressures can be matched with the predicted pressures determined directly based on the aforementioned conversion relationship. Similarly, at least one correction factor characterizing the aforementioned offset error can be determined, achieving sufficient accuracy. In this way, in the event of sensor failure, abnormal detection data, or sensor unavailability, the corrected pressure data can be determined through step 330 above, based on the conversion relationship and correction factor. This will make up for the lack of pressure data during the aforementioned sensor malfunction period.

[0197] In some cases, the blood pump device includes a pressure sensor, but this pressure sensor is not continuously available; that is, the pressure sensor has both an operating mode and a shutdown mode. For example, the sensor requires periodic maintenance, such as periodic flushing. During flushing, the pressure data detected by the pressure sensor is inaccurate, so the pressure data during this period is deactivated, and step 330 above is performed in the shutdown mode.

[0198] The method of determining or estimating the inlet and outlet pressures of the pump head, based on either sensor measurement or physiological effects, is applicable to blood pump devices where no pressure sensor is located at the pump head, as well as those where a pressure sensor is present at the pump head. For example... Figure 2The illustrated interventional blood pump uses an arterial pressure sensor housed within the handle of a drive catheter located outside the target patient's body. This sensor detects the target patient's arterial pressure through a gap between the interventional sheath and the blood vessel. Therefore, the aortic pressure, i.e., the pump head outlet pressure, can be detected by this arterial pressure sensor, while the ventricular pressure, i.e., the pump head inlet pressure, can be estimated based on relevant physiological effects. For example, the physiological effect that ventricular pressure is approximately equal to aortic pressure when the aortic valve is open during a cardiac cycle. Of course, arterial pressure can also be detected using a separate external detection device; this application does not limit this, as long as one of the pump head's inlet and outlet pressures can be measured using a sensor, and the other can be determined or estimated based on physiological effects. For example, the pressure data to be predicted is net pressure, derived from the difference between the determined outlet and inlet pressures. In one possible scenario, the patient's aortic pressure can be measured, and the clinician can know the left ventricular diastolic pressure from previous measurements or estimate / calculate from other physiological conditions (and input into the blood pump's electronic system or calculated by the system from other measurements) to provide an accurate value (actual value) of the net pressure, which can be used to calculate offset errors.

[0199] The determination of the aforementioned correction factor requires the occurrence of one or more of the aforementioned conditions. The blood pump can adjust its operating state to a calibrated operating state to satisfy the conditions for the occurrence of one or more of these conditions. In this way, during the period when the blood pump device is in calibrated operating state, one or more of the aforementioned conditions can occur or occur, so that the device can determine the aforementioned correction factor.

[0200] The aforementioned calibration operation can be performed in the background by the electronic equipment of the blood pump device during normal operation. For example, if the blood pump device is equipped with a pressure sensor, the blood pump device can record the pressure data detected by the sensor to record the actual pressure of the pump head and determine the aforementioned calibration factor. In the event of sensor failure or large detection error, step 330 can be performed based on the calibration factor to accurately predict the pressure of the pump head.

[0201] The aforementioned calibration operation state can also be entered by adjusting the pump speed of the blood pump device. Specifically, the pump speed of the blood pump device is controlled to enter the calibration operation state to meet one or more conditions. The triggering timing for controlling the pump speed of the blood pump device to enter the calibration operation state can be during the initial startup phase of the blood pump device or during the operation of the blood pump device. Specific control methods are described below and will not be introduced here.

[0202] Under the above-mentioned corrective operating conditions, one or more conditions can occur, so the actual pressure corresponding to the pump head can be determined, measured or estimated. Accordingly, using the actual pressure as a reference, at least one correction factor can be determined or updated under the corrective operating conditions.

[0203] The control efficiency of entering the above-mentioned corrective operating state by adjusting the pump speed is high, requiring no complex control calculations, and the control stability is high.

[0204] In an exemplary embodiment, the aforementioned correction factor can be detected and determined during the process of the blood pump device assisting the target object. For example, during the process of the blood pump device assisting the target object, the pressure corresponding to the pump head is detected, and the detected pressure is compared with the actual pressure to obtain the aforementioned correction factor. This application embodiment does not limit the method of obtaining the correction factor.

[0205] In one example, the process of obtaining the above correction factor, i.e., step 320 above, may specifically include the following steps:

[0206] During the calibration operation, operational signal data samples are acquired. These operational signal data samples include operational signal data collected when the blood pump device is in the calibration operation state. The operational signal data collected during this phase can be used as sample data to determine the calibration factor, i.e., the aforementioned operational signal data samples.

[0207] The operating signal data samples are transformed to obtain the predicted pressure data samples corresponding to the pump head. Specifically, after obtaining the above operating signal data samples, they can be directly converted into predicted pressure data according to the above transformation relationship. The predicted pressure data here is the pressure prediction data obtained directly from the above operating signal data samples.

[0208] Identify feature points in the predicted pressure data sample that are associated with one or more scenarios. These scenarios are related to pressure waveform characteristics and time; therefore, these feature points can be determined by identifying pressure waveform characteristics or performing timestamp matching. For example, to determine feature points under aortic valve opening conditions, it is necessary to identify the pressure waveform characteristics at the pump head under aortic valve opening conditions. When the heart contracts to a certain extent, the left ventricular pressure increases. When it increases to a certain level, the ventricle squeezes blood, opening the aortic valve with higher ventricular pressure. At this point, the ventricular pressure should be at a higher point, which can be recorded as a pressure waveform feature. In addition, when the aortic valve is open, the left ventricle is connected to the aorta, so the left ventricular pressure is basically the same as the aortic pressure, which can also be considered a pressure waveform feature. Furthermore, the fact that the left ventricular pressure and aortic pressure are basically the same also means that the net pressure at the pump head is approximately 0, which can also be considered a pressure feature. Therefore, feature points in the predicted pressure data can be determined based on the above pressure waveform characteristics. On the other hand, the predicted pressure data can also be matched with the actual pressure data collected by the sensor based on the timestamp, identifying feature points where the predicted pressure data and the actual pressure data collected by the sensor match. This application does not limit this approach.

[0209] A correction factor is determined based on the predicted pressure corresponding to the feature point and the actual pressure corresponding to one or more scenarios. Optionally, the difference between the predicted pressure and the actual pressure, i.e., the determined offset error, is used as the above correction factor to correct the offset error.

[0210] There are various types of correction factors, including but not limited to operating signal correction factors, conversion relationship correction factors, and pressure data correction factors. Operating signal correction factors represent correction factors corresponding to operating signal data, which can correct the operating signal data. Conversion relationship correction factors represent correction factors corresponding to the conversion relationship between operating signal data and predicted pressure data, which can correct the conversion relationship. The predicted pressure data mentioned above is the predicted pressure obtained by converting operating signal data based on the conversion relationship. Pressure data correction factors represent correction factors corresponding to predicted pressure data, which can correct the predicted pressure data.

[0211] Optionally, the types of at least one correction factor include, but are not limited to, at least one of the following:

[0212] Offset value, scaling factor.

[0213] Optionally, the pressure data correction factor includes, but is not limited to, a fixed pressure offset value and a speed-related pressure offset value. The pressure offset value characterizes the offset error between the predicted pressure and the actual pressure corresponding to the pump head. Furthermore, different speeds can correspond to different pressure offset values; therefore, the aforementioned speed-related pressure offset value includes the pressure offset value corresponding to each operating speed.

[0214] Optionally, the operating signal correction factor includes, but is not limited to, at least one of a fixed current offset value and a speed-related current offset value. Where the above conversion relationship characterizes the conversion relationship between the operating signal and the pressure at the pump head, the data object to be corrected can be the input current data, and therefore the correction factor can be the current offset value.

[0215] Optionally, the aforementioned scaling factors include, but are not limited to, fixed scaling factors and speed-related scaling factors. When using the aforementioned scaling factors as correction factors, the object to be corrected can be at least one of operating signal data, conversion relationships, and predicted pressure data. The scaling factor can adjust at least one data item in the object to be corrected based on the scaling factor.

[0216] In addition, the aforementioned correction factors can be preset. For example, the blood pump device has undergone hydraulic testing before leaving the factory. During the hydraulic testing, the blood pump device can operate under the aforementioned calibrated operating conditions. The resistance device of the blood pump device is processed accordingly, and the determined correction factors are stored in the storage medium.

[0217] After obtaining at least one of the above correction factors, since the above correction factors can characterize the offset error between the predicted pressure and the actual pressure corresponding to the pump head, they can be used as input data and introduced into the conversion process of converting the blood pump operation signal into pressure data at the pump head. This corrects the offset error caused by factors such as individual differences of the target object and individual differences of the blood pump device. Thus, under the current operating conditions of the blood pump device, more accurate, reliable, and more consistent pump head pressure data with the current target object can be obtained through conversion processing based on the correction factors.

[0218] Furthermore, the technical solution provided in this application embodiment is not only applicable to blood pump devices without relevant sensors at the pump head, but also applicable to blood pump devices with relevant sensors at the pump head. In the case of failure or abnormal detection of the relevant sensors in the latter, the above method can still be used to predict the pressure at the pump head.

[0219] Furthermore, predicting pump head pressure is more accurate than directly predicting flow-related data based on operational signal data. This is because the pump head pressure signal contains the aforementioned characteristic points (i.e., reference points) that can be used to eliminate or estimate the aforementioned offset errors. When certain data indicators are correlated with pressure, their accuracy is better than that of data indicators correlated with flow rate, because predicting pump head pressure data allows the device to make clearly defined references based on relevant physiological characteristics or pressure sensor detection data. This allows the actual pressure corresponding to certain characteristic points in the pressure waveform to be determined or estimated, such as the relationship between aortic pressure and left ventricular pressure when the aortic valve is open.

[0220] In one possible embodiment, the predicted pump head pressure data may specifically be the pump head net pressure data, where the actual reference value for the pump head net pressure should be approximately 0 when the aortic valve is open. See [reference needed] for details. Figure 4 , Figure 4 An illustrative diagram shows the actual cardiac pressure curve under normal aortic valve opening and closing conditions. Figure 4 As shown, with the aortic valve open, the actual left ventricular pressure curve roughly coincides with the actual aortic pressure curve, while the actual net pressure curve of the pump head is close to 0. Therefore, it can be considered that with the aortic valve open, the left ventricular pressure is equal to the aortic pressure, or the net pressure of the pump head is approximately equal to 0, which is physiologically consistent with cardiac hemodynamics.

[0221] Therefore, the predicted net pressure data curve at aortic valve opening can be compared with the actual net pressure data to determine the net pressure deviation error, i.e., to obtain the net pressure correction factor. In subsequent operation, this correction factor is used for conversion processing to obtain the corrected pump head net pressure data. Specifically, as follows... Figure 5 As shown, Figure 5 An exemplary schematic diagram of the pump head pressure prediction curve under normal aortic valve opening and closing conditions is shown. Figure 5 The pump head predicted net pressure curve is shown, compared to Figure 4 The actual net pressure curve of the pump head shown clearly shows... Figure 5 The pump head predicted net pressure curve shown is offset; that is, the predicted net pressure curve is not close to 0 during aortic valve opening. Therefore, by comparing the pump head predicted net pressure data with a reference actual net pressure data (e.g., 0), the net pressure correction factor ΔP can be determined.

[0222] Furthermore, during blood pump operation, based on the reference relationship that the actual reference value of the pump head net pressure should be approximately 0, the predicted pump head net pressure can be periodically corrected to zero, thereby improving the accuracy of the pump head net pressure in real time. The pump head net pressure waveform is also a useful signal for clinicians and can be used to determine other pressure parameters, such as left ventricular pressure. Net pressure data can also be used to detect the physiological state of the target, such as the aortic valve opening cycle and stenosis level. Further, the pump head net pressure can be used to check whether the pump is being used safely, for example, within its pressure rating and without the risk of backflow. In summary, using pump head net pressure data as the prediction target in this embodiment can meet multiple data detection needs while ensuring the accuracy of the predicted data.

[0223] There are several implementation methods for the conversion and processing between the blood pump operation signal data and the pressure data at the pump head, which will be introduced below.

[0224] In one possible implementation, the operating signal data of the blood pump device can be converted first, and then the converted predicted pressure data can be corrected according to the aforementioned correction factor. Accordingly, in this implementation, step 330 may include the following steps:

[0225] The operating signal data is converted and processed to obtain the predicted pressure data corresponding to the pump head; the predicted pressure data is corrected based on at least one correction factor to obtain the corrected pressure data.

[0226] Optionally, the specific operation of correcting the predicted pressure data described above can be: applying at least one correction factor to correct the offset error of the predicted pressure data to obtain corrected pressure data.

[0227] Please refer to Figure 6 , Figure 6 An exemplary diagram illustrates the application of a net pressure correction factor to correct offset errors in the pump head net pressure prediction data curve. For example... Figure 6 As shown, according to Figure 5 The net pressure correction factor ΔP determined in the calculation is used to shift the predicted net pressure curve of the pump head, thus obtaining the corrected net pressure curve of the pump head. The corrected net pressure curve of the pump head is then compared with... Figure 4 The actual net pressure curve of the pump head shown is close to that of the pump head.

[0228] In this approach, after obtaining the aforementioned correction factor, the offset error can be subtracted from the predicted pressure data determined based on the above conversion relationship to achieve the offset error correction, thereby generating a set of corrected pressure data. The corrected pressure data is substantially similar to the actual pressure waveform corresponding to the pump head of the blood pump device. In some cases, since the reference actual pressure is estimated based on physiological characteristics, the offset error determined in this way may not be completely consistent with the actual error. However, even in these cases, applying the aforementioned correction factor to correct the offset error will make the predicted pressure data closer to the true pressure value.

[0229] In another possible implementation, the operating signal data of the blood pump device can be corrected first, and then converted. Accordingly, in this implementation, step 330 above may include the following steps:

[0230] Based on at least one correction factor, the operating signal data is corrected to obtain corrected operating signal data; the corrected operating signal data is then converted to obtain the corrected pressure data corresponding to the pump head.

[0231] Optionally, the specific operation of correcting the running signal data described above can be: applying at least one correction factor to correct the offset error of the running signal data to obtain corrected running signal data.

[0232] In some cases, the operating signal data can be modified in advance. The predicted pressure data corresponding to the modified operating signal data after conversion can be approximately equal to the actual pressure data corresponding to the original operating signal data under the current operating conditions.

[0233] In another possible implementation, a pump head pressure prediction model can be obtained, and the above-mentioned conversion process can be performed based on the pump head pressure prediction model. The pump head pressure prediction model characterizes the conversion relationship between the operating signal of the blood pump device and the pump head pressure.

[0234] Optionally, the generation process of the above-mentioned pump head pressure prediction model includes:

[0235] Obtain operating signal test data samples and corresponding pump head pressure detection data samples; generate a pump head pressure prediction model based on the operating signal test data samples and pump head pressure detection data samples.

[0236] The aforementioned operational signal test data samples and their corresponding pump head pressure detection data samples can be data samples collected during experiments. For some blood pump devices equipped with pressure sensors, these sample data can also be data samples collected during the operation of the blood pump device. Alternatively, the aforementioned data samples may include not only data samples collected during experiments but also data samples collected during the operation of the blood pump device. This application embodiment does not limit this, nor does it limit the type of pump head pressure prediction model. Those skilled in the art can select the best prediction model based on the prediction effects of various models.

[0237] Optionally, the pump head pressure prediction model includes, but is not limited to, at least one of the following:

[0238] Linear relational models, non-linear relational models, lookup tables, and machine learning models.

[0239] In the above conversion process based on the pump head pressure prediction model, the conversion can be performed first and then corrected; alternatively, the input data of the model can be corrected first and then the conversion can be performed; or the model itself can be corrected. Those skilled in the art can choose the appropriate method based on the actual situation. Accordingly, step 330 includes the following steps:

[0240] The operating signal data is input into the pump head pressure prediction model for conversion processing, and the predicted pressure data corresponding to the pump head is output. Based on at least one correction factor, the predicted pressure data is corrected to obtain the corrected pressure data.

[0241] Alternatively, the operating signal data can be corrected based on at least one correction factor to obtain corrected operating signal data; the corrected operating signal data can then be input into the pump head pressure prediction model for conversion processing to output corrected pressure data.

[0242] Alternatively, the pump head pressure prediction model can be corrected based on at least one correction factor to obtain a corrected pump head pressure prediction model; the operating signal data can be input into the corrected pump head pressure prediction model for conversion processing to output corrected pressure data.

[0243] In an exemplary embodiment, the aforementioned operating signal data may be the rotational speed signal data corresponding to the blood pump device, and the aforementioned corrected pressure data may be the corrected net pressure data of the pump head. In the blood pump device, current data and rotational speed signal data are relatively easy-to-detect data indicators. If the aforementioned conversion processing is performed using rotational speed signal data, the current sensor of the blood pump device can be removed, reducing the number of sensors in the system (or the bandwidth / quality of the sensors), thereby reducing the cost and complexity of the electronic equipment, and in some cases, alternative motor types can be used. Furthermore, avoiding the use of current signals in the signal processing system of the blood pump device can reduce its resource usage and complexity. Even in current-based motor control schemes, the rotational speed signal is a fundamental measurement signal of the controlled device, therefore the relevant information has a higher bandwidth and generally lower noise.

[0244] Specifically, the aforementioned rotational speed signal data can be the speed of the motor and / or impeller in the blood pump device. In some blood pump system designs (from calculations or experiments), the rotational speed signal varies little with the long-term average value of the pump head net pressure. From system analysis, a conversion relationship between the measured speed change and the pump head net pressure can be found, such as the pump head pressure prediction model mentioned above. This model can then be used to convert the measured motor speed while the device is used to estimate the net pressure between the pump inlet and outlet within the target body. Depending on the calculated or measured pump system performance, various types of models can be used. For some types of pump systems, a simple linear relationship may perform well, while for other types, nonlinear models or lookup table models based on search lists may be more effective. If the computational power of the blood pump device meets the computational requirements of the machine learning model, the machine learning model can also predict the aforementioned pump head pressure.

[0245] In some systems, due to the characteristics of the mechanical transmission system used, such as magnetic coupling transmission system or eddy current coupling system, the speed of the drive motor and the speed of the impeller may be different. In these cases, the motor speed or the impeller speed can be converted. Converting each speed requires a slightly different pump head pressure prediction model.

[0246] Using the measured rotational speed signal as the driver for the net pressure signal is useful here because the speed measurement signal is directly affected by the hydraulic system without requiring any intermediate modifications to the electrical system, as is the case with current measurements. The mechanical system has similar frequency characteristics to the hydraulic system, which helps avoid higher-frequency interference that may occur in current measurements, such as PWM driver and high-frequency controller noise, resulting in more accurate predictions of the net pressure data.

[0247] The basis for correcting net pressure is to identify a characteristic point at which the aortic valve opens within the net pressure prediction data, thereby performing zero-point correction. The technique for correcting offset errors using cardiac physiological information must be able to clearly measure a signal that includes at least the patient's heart rate. This is typically less than 2 or 3 Hz (Hertz), and the velocity measurement system should have at least this bandwidth, but preferably 10 times or, ideally, 100 times. When using variations in long-term averages, applying a high-pass filter to the velocity signal with a cutoff frequency significantly lower than the patient's expected heart rate, such as 0.05 or 0.1 Hz, can be helpful. The measurement accuracy should also be at least 10, 100, or 1000 divisions within the expected velocity variation caused by changes in patient pressure within the expected working physiological range to provide a high-resolution net pressure signal. Additionally, efforts should be made to keep the noise of the velocity sensor to a minimum.

[0248] As mentioned above, the pump head pressure prediction model can determine the uncorrected net pressure signal based on the measured velocity signal. This model can be linear or nonlinear, and can be based on a lookup table, depending on the pump's hydraulic characteristics and other factors in the pump system, as well as the trade-off between estimation accuracy and model computational complexity. In the simplest linear model, the uncorrected pressure is proportional to the motor speed, as shown in the following equation:

[0249] P net，uc =Kω r

[0250] Among them, P net，uc This is the uncorrected net pressure (typically -10…+150 mmHg), ω r Where K is the impeller speed (typically 1000…100000 revolutions per minute (rpm)), and K is a constant. In some cases, the pump system characteristics can be directly calculated or simulated to give a suitable model. In other cases, it may be helpful to conduct experiments based on the development process and derive the model in this way.

[0251] In some cases, variations exist between manufactured blood pump devices. In these situations, it is beneficial to customize the model for an individual pump or pump batch by calibrating some parameters in the model based on production test results. The aforementioned pump head pressure prediction model can be obtained by adjusting the parameters of the original pump head pressure prediction model based on hydraulic test results. For example, in a linear model, some proportionality constants may be changed from pump to pump. Storing calibration constants within the pump itself can be helpful, for example, in memory or in a human- and / or machine-readable label on the product.

[0252] In some cases, further refining the model to account for the patient's specific physiological condition is useful. For example, if the clinical team knows the blood viscosity, they can input it into the system to modify the model parameters, resulting in more accurate results. The blood pump device can acquire the target patient's blood viscosity data and then perform conversion processing based on at least one correction factor, the blood viscosity data, and the operating signal data to obtain the corrected pressure data corresponding to the pump head. Optionally, the model parameters of the pump head pressure prediction model are adjusted based on the blood viscosity data to obtain a pump head pressure prediction model that matches the current blood viscosity. Based on the adjusted pump head pressure prediction model, at least one correction factor and the operating signal data are converted to obtain the aforementioned corrected pressure data. The process of converting and correcting the operating signal data based on the correction factor to obtain the pump head pressure data can be found above and will not be repeated here.

[0253] Known blood pressure, such as the aortic valve opening blood pressure, can also be used to improve the accuracy of models and predictions.

[0254] The method described above uses blood pump velocity as the input signal, converts it to net pressure, and then performs offset error correction. Other available signals can also be converted to net pressure signals, and then offset error correction can be performed using variations in the method, as described below.

[0255] In one implementation, the speed error (actual speed - user's target speed) can be used instead of the speed signal described above. This eliminates some constant offset in the speed signal and, in some cases, improves the numerical accuracy of the calculation.

[0256] In one implementation, a torque sensor is used to provide a signal related to the pump's net pressure. This can be advantageous because the accuracy and noise level of such a sensor can be better than using a signal derived from current. Types of torque sensors include strain gauges, spring balances, etc. This approach also has the advantage that torque is the primary mechanical signal, thus offering a fast response time and minimal susceptibility to control system noise.

[0257] In one implementation, for some blood pump devices using eddy current magnetic couplers, a signal with a good correlation to the pump net pressure can be found by measuring the speed difference between the two shafts of the eddy current coupler (the drive motor and the intervention pump rotor), i.e., the aforementioned coupled speed difference data. This speed difference signal is approximately proportional to the torque of the load. It can then be used as input to a net pressure prediction model. The advantage of this is that implementing speed difference measurement in pumps using this type of coupler may be cheaper than using torque measurement, and it can provide a better and simpler conversion relationship than directly using either the motor speed or the impeller speed.

[0258] In one implementation, motor controller currents can be used. Since controllers typically use various control actions to achieve their final output (e.g., "PID" controllers use proportional, integral, and derivative components), in some pump configurations, at least one current parameter of these controller currents, particularly the proportional term current (determined empirically), correlates better with the pump net pressure than the entire controlled motor current, allowing for the use of a more accurate model with less interference. Another useful parameter, which can be extracted from certain types of control systems, is the orthogonal current term found by applying the Clarke-Parker transform to the phase or line current of the motor.

[0259] In one implementation, the entire motor current can be used as a driver for net pressure estimation, such as the peak or RMS phase or line of a single motor phase or line, or the average of these parameters for some or all phases of the motor. This value can be used if there is a reasonable correlation between current and net pressure in the system configuration.

[0260] In an exemplary embodiment, after obtaining the aforementioned calibrated pressure data, further signal statistical analysis can be performed on the calibrated pressure data to obtain pressure parameter indicators useful to users, facilitating the observation of the target object's physiological condition and equipment operation. This statistical information will be directly provided to the user to trigger alarms or as input for further calculation steps.

[0261] Optionally, the above method may also include, but is not limited to, at least one of the following steps:

[0262] Determine the average net pressure corresponding to the corrected pressure data over a fixed time period;

[0263] Determine the average net pressure corresponding to the target number of heartbeat cycles for the corrected pressure data;

[0264] Determine the root mean square net pressure value corresponding to the corrected pressure data over a fixed time period;

[0265] Determine the root mean square net pressure value corresponding to the target number of heartbeat cycles for the corrected pressure data;

[0266] Determine the amplitude of the net pressure fundamental frequency component corresponding to the corrected pressure data over a fixed time period;

[0267] Determine the amplitude of the net pressure fundamental frequency component corresponding to the target number of heartbeat cycles of the corrected pressure data;

[0268] The spectrum of the net pressure waveform corresponding to the corrected pressure data is determined by various methods, including Fast Fourier Transform (FFT).

[0269] Besides the pressure parameters mentioned above being determined based on calibrated pressure data, the calibrated pressure data and the aforementioned statistical information can also be used in other ways to meet various practical needs. Specifically, the above method also includes, but is not limited to, at least one of the following steps:

[0270] Display the calibration pressure data and / or the above statistical information.

[0271] Alarm information is triggered based on calibrated pressure data and / or the aforementioned statistical information; for example, an alarm is activated to warn the user of unwanted pump operation, such as excessively high or low pressure levels.

[0272] Left ventricular pressure data is determined based on the corrected pressure data and aortic pressure data; wherein, the pump head of the blood pump device is placed between the left ventricle and the aorta, and the aortic pressure data is obtained from the detection module corresponding to the blood pump device, which can be a pressure sensor in the blood pump device or in other devices;

[0273] The calibrated pressure data is converted to obtain the pump flow rate indication data corresponding to the blood pump device. Optionally, the pump head net pressure signal is connected to the flow rate model to provide an estimate of the pump flow rate.

[0274] Based on the calibrated pressure data, the pump position indication information is determined. In some cases, the pump head is placed between the aorta and the left ventricle. In the correct position, the pump head inlet is located in the left ventricle, and the pump head outlet is located in the aorta. The aortic valve will periodically open and close, so the net pressure data of the pump head will also have large periodic fluctuations, meaning the amplitude of the net pressure data will fluctuate beyond a certain threshold. However, in the incorrect position, such as when both the pump head inlet and outlet are located in the aorta, or both are located in the left ventricle, the fluctuation of the net pressure data is smaller because the pressure at the pump head inlet and outlet is essentially the same, approximately equal to the aortic pressure or the left ventricular pressure. Therefore, the correctness of the blood pump device's intervention position can be determined by judging the amplitude of the calibrated net pressure data. If the amplitude of the net pressure data is greater than the amplitude threshold corresponding to the correct position, the blood pump device is determined to be in the correct intervention position; otherwise, the blood pump device is determined to be in the incorrect intervention position, and an incorrect pump position warning message can be issued.

[0275] The above section introduces some methods for detecting blood pump pressure information and related applications. It mentions the operation of controlling the pump speed of the blood pump device to enter the calibration operation state. This part involves the control of the blood pump, and the control part will be explained below.

[0276] Please refer to Figure 7The diagram illustrates a flowchart of a blood pump control method provided in one embodiment of this application. The method may include the following steps (710-730).

[0277] Step 710: Control the pump speed of the blood pump device to enter the calibration operation state.

[0278] Among them, one or more situations in which the actual pressure corresponding to the pump head can be determined, measured or estimated can occur under the corrected operating state;

[0279] The purpose of entering the above-mentioned calibration operation state is to ensure that one or more conditions, such as the actual pressure corresponding to the pump head being determined, measured, or estimated, can occur. Therefore, the first target speed can be used as the target speed of the blood pump device, and the blood pump device is controlled to be in the calibration operation state based on the first target speed. The first target speed satisfies the speed conditions for the occurrence of one or more of the above-mentioned conditions. In this application embodiment, the specific speed setting of the first target speed is not limited.

[0280] During calibration operation, the calibration factor can be determined according to the method described in the above embodiments for subsequent pressure data calibration.

[0281] Step 720: In response to the end of the calibration operation, update the control target of the blood pump device.

[0282] Step 730: Control the blood pump device to operate based on the updated control target.

[0283] After one or more of the above situations occur, such as after one or more of the above situations occur within a few heartbeat cycles or a certain period of time, the control target of the blood pump device can be updated to enter the normal operating state, and the blood pump device can be controlled to operate based on the updated control target.

[0284] The aforementioned control targets include, but are not limited to, target rotational speed, target flow rate, target pressure, and target support level.

[0285] In the technical solution provided in this application embodiment, by controlling the pump speed of the blood pump device, the blood pump can be controlled to enter a calibration operation state. In the calibration operation state, one or more conditions can be normally determined, measured, or estimated regarding the actual pressure corresponding to the pump head. The blood pump device can then obtain the actual pressure corresponding to the pump head in the calibration operation state, improving the accuracy of blood pump pressure detection. Furthermore, the calibration operation state is temporary, and the control target of the blood pump device can be automatically updated, obtaining accurate pressure information without affecting the normal use of the blood pump device.

[0286] Furthermore, regardless of whether the blood pump device is equipped with a pressure sensor, under the aforementioned calibration operating state, the blood pump device can determine the actual pressure corresponding to the pump head, which can provide accurate pressure reference information for the pressure detection of the blood pump device, so that the blood pump device can perform more operations, such as sensor anomaly detection, pressure data calibration, etc.

[0287] During the startup and operation phases of the blood pump, the pump speed of the blood pump device can be controlled to enter the calibration operation state.

[0288] During the blood pump startup phase, step 710 above may include the following operations:

[0289] In response to the blood pump start command, the blood pump device is started, and the rotation speed of the blood pump device is controlled to increase to the first target rotation speed; the operation of the blood pump device is controlled based on the first target rotation speed.

[0290] The calibration operation status includes the state in which the blood pump device operates based on the first target speed;

[0291] The aforementioned first target rotational speed is a relatively low target speed. The purpose of controlling the blood pump device based on this first target rotational speed is to prevent the aortic valve from ceasing to open under high support levels from the blood pump device. In the above embodiments, one or more situations include the aortic valve opening during the cardiac cycle, in which case the left ventricular pressure and aortic pressure are essentially the same. This means that during the phase when the aortic valve remains open, if either the left ventricular pressure or the aortic pressure is known, the other can also be known to be estimated as the same pressure as the former, or the net pressure corresponding to the pump head can be known to be estimated as 0, thus obtaining the actual pressure that can be used to determine the offset error. If the blood pump rotational speed is high, a large amount of blood in the left ventricle is drawn into the pump head, resulting in lower left ventricular pressure, which may pose a risk of the aortic valve permanently closing and never opening again. In the case where the aortic valve no longer opens, it is difficult to estimate the relevant pressure based on the relationship that the left ventricular pressure and aortic pressure are essentially the same. Therefore, it is necessary to control the blood pump device to operate at a relatively low first target rotational speed for a period of time during the startup phase.

[0292] Optionally, the blood pump device operates at a first target rotational speed for a first duration. The length of the first duration is greater than the length of at least two heartbeat cycles, so that the electronic equipment of the blood pump device can collect pressure data at multiple feature points in the calibration operation state, thereby determining the at least one calibration factor.

[0293] When the calibration operation is complete, the target speed of the blood pump device can be adjusted from the first target speed to the second target speed, and the operation of the blood pump device can be controlled based on the second target speed. The second target speed refers to the target speed set based on the control operation.

[0294] After the blood pump device determines the above-mentioned correction factor, or after the blood pump device runs at the first target speed for a first duration, the blood pump device can automatically adjust the target speed, thereby adjusting the target speed of the blood pump from the first target speed to the second target speed set by the control operation, thereby switching the blood pump device from the above-mentioned correction operation state to the normal operation state.

[0295] The aforementioned control operation can be either a speed control operation or a blood pump start-up operation. If the user starts the blood pump without setting an additional speed, then the second target speed mentioned above is the default target speed corresponding to the blood pump start-up operation. If the user performs a speed control operation after starting the blood pump, such as adjusting the speed knob, then the second target speed mentioned above is the target speed set by the speed control operation mentioned above.

[0296] Optionally, the first target speed is less than or equal to the second target speed. In one possible implementation, the first target speed is the minimum operating speed of the blood pump device. In another possible implementation, the default target speed is the minimum operating speed of the blood pump device. In yet another possible implementation, both the first target speed and the default target speed are the minimum operating speeds of the blood pump device.

[0297] After adjusting the target speed to the second target speed, the blood pump device can be controlled to operate based on the aforementioned second target speed.

[0298] Furthermore, during the startup phase of the blood pump device, the blood pump starts rotating from zero, first reaching the first target speed and running for a certain period of time before reaching the second target speed. This does not affect the normal startup of the blood pump, and at the same time, the above-mentioned correction factor can be determined imperceptibly, without requiring the user to perform any additional correction operations.

[0299] Besides entering the calibration operation state during startup, the blood pump can also re-enter the calibration operation state during operation to update the aforementioned calibration factors. As mentioned earlier, the offset error is fixed under certain operating conditions. For example, if the mechanical load of the blood pump device does not change within a certain period of time, the offset error will remain essentially the same. However, if the mechanical load of the blood pump device changes, the offset error represented by the calibration factors determined in the previous stage may not match the actual offset error caused by the current load. Therefore, the blood pump can re-enter the aforementioned calibration operation state during operation to update the aforementioned calibration factors based on the actual situation.

[0300] Specifically, step 710 above may also include the following operations:

[0301] During the operation of the blood pump device, the target rotational speed of the blood pump device is adjusted to a first target rotational speed; the operation of the blood pump device is controlled based on the first target rotational speed. During the operation of the blood pump, the target rotational speed of the blood pump device can be adjusted from the second target rotational speed to the first target rotational speed to enter the correction operation state, and the correction operation state is maintained for a second duration. The second duration can be less than, equal to, or greater than the first duration, and the time required to update the correction factor can be determined according to the actual equipment; this application embodiment does not limit this.

[0302] The calibration operating state includes the state in which the blood pump device operates based on the first target speed.

[0303] The triggering conditions for entering the above-mentioned calibration operation state can be: receiving a calibration command during the operation of the blood pump device, reaching the calibration cycle, or detecting an abnormality in the target parameter of the blood pump device, and adjusting the target speed of the blood pump device to the first target speed.

[0304] When not initially determining the calibration operation state, the blood pump device may enter the calibration operation state to update the calibration factor based on a calibration command triggered by a manual calibration operation received through its user interface, or it may automatically update the calibration factor periodically, or it may enter the calibration operation state to update the calibration factor when an abnormality in the target parameter is detected. This application embodiment does not limit the triggering conditions for the blood pump device to update the calibration factor.

[0305] Optionally, the aforementioned target parameters include, but are not limited to, blood pump operating parameters that can characterize changes in mechanical load, and physiological parameters of the target object.

[0306] For example, in one possible implementation, the target parameter could be a blood pump operating parameter that characterizes changes in mechanical load, such as a current parameter. If the target rotational speed of the blood pump remains unchanged, but the blood pump device detects an increase in the blood pump current data exceeding a first threshold, it can be assumed that the mechanical load on the blood pump device has increased. In this case, the correction factor may not accurately represent the offset error caused by the current load condition, and therefore the device can re-enter the aforementioned correction operation state.

[0307] In another possible implementation, the target parameter can be a physiological parameter of the target object, such as the pressure parameter within the heart where the pump head is located. For example, if the relevant pressure data of the target object detected by the blood pump device is severely distorted, or if the difference between the value detected by the additional detection equipment is greater than a second threshold, the blood pump device itself or the user can consider the current pressure data prediction to be abnormal, and thus can re-enter the above-mentioned correction operation state.

[0308] In addition to the triggering conditions mentioned above, or based on those conditions, the electronic equipment of the blood pump device can also issue a calibration prompt during the operation of the blood pump device. The user can then decide whether calibration is necessary based on this prompt. If the electronic equipment receives a confirmation operation (i.e., receives confirmation information), the device can adjust the target speed of the blood pump device to the first target speed in response to the confirmation message for the calibration prompt.

[0309] Optionally, the electronic equipment of the blood pump device can issue a calibration prompt message when the blood pump device reaches the calibration cycle or when the target parameter in the blood pump device is detected to be abnormal;

[0310] In response to the confirmation operation of the calibration prompt information, the target speed of the blood pump device is adjusted to the first target speed.

[0311] Because the blood pump device needs to run at a lower first target speed for a period of time during calibration operation, and the first target speed may be lower than the second target speed set by the user, the device can issue calibration prompts to remind the user that the data prediction accuracy of the device may have decreased. On the other hand, it can also provide the user with a speed reduction prompt message, which indicates that the speed will decrease during calibration operation. This allows the user to decide whether to re-enter calibration operation, preventing the blood pump device from automatically reducing its support level and improving the safety of the device.

[0312] The aforementioned prompts can be issued based on the user interface of the blood pump device, such as icon prompts, text prompts, or voice prompts. The aforementioned confirmation operation can be an operation performed by the user based on the aforementioned prompts to correct data; this application embodiment does not limit the operation method of the confirmation operation.

[0313] The following are embodiments of the apparatus of this application, which can be used to execute embodiments of the method of this application. For details not disclosed in the apparatus embodiments of this application, please refer to the embodiments of the method of this application.

[0314] Please refer to Figure 8 This diagram illustrates a block diagram of a blood pump pressure information detection device according to an embodiment of this application. The device has the function of implementing the above-described blood pump pressure information detection method; the function can be implemented in hardware or by hardware executing corresponding software. The device can be a computer device or can be installed within a computer device. The device 800 may include:

[0315] The data acquisition module 810 is used to acquire the operating signal data of the blood pump device during the operation of the blood pump device assisting the target object. The blood pump device includes a pump head.

[0316] The correction factor acquisition module 820 is used to acquire at least one correction factor corresponding to the target object; wherein the correction factor characterizes the error between the predicted pressure and the actual pressure corresponding to the pump head; the correction factor is determined when the blood pump device is in a calibration operation state, the calibration operation state including one or more situations in which the actual pressure corresponding to the pump head can be determined, measured or estimated;

[0317] The pressure conversion and correction module 830 is used to perform conversion processing based on the at least one correction factor and the operating signal data to obtain the corrected pressure data corresponding to the pump head.

[0318] Please refer to Figure 9 This diagram illustrates a block diagram of a blood pump control device according to an embodiment of this application. The device has the function of implementing the above-described blood pump control method; the function can be implemented in hardware or by hardware executing corresponding software. The device can be a computer device or can be installed within a computer device. The device 900 may include:

[0319] The blood pump control module 910 is used to control the pump speed of the blood pump device to enter the calibration operation state; wherein, one or more of the actual pressure corresponding to the pump head can be determined, measured or estimated in the calibration operation state.

[0320] The control target update module 920 is used to update the control target of the blood pump device in response to the end of the calibration operation state.

[0321] The blood pump control module 910 is also used to control the operation of the blood pump device based on the updated control target.

[0322] It should be noted that the apparatus provided in the above embodiments is only illustrated by the division of the above functional modules when implementing its functions. In practical applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above. In addition, the apparatus and method embodiments provided in the above embodiments belong to the same concept, and the specific implementation process can be found in the method embodiments, which will not be repeated here.

[0323] One embodiment of this application provides an electronic device. This electronic device can be a control console in a blood pump device, or a computer device within a flushing device of a blood pump device. The electronic device includes a processor and a memory, wherein the memory stores at least one instruction, at least one program, a code set, or an instruction set. The at least one instruction, the at least one program, the code set, or the instruction set is loaded and executed by the processor to implement the blood pump pressure information detection method and / or blood pump control method provided in the above embodiment.

[0324] Specifically:

[0325] Typically, electronic devices include a processor and memory.

[0326] The processor may include one or more processing cores, such as a quad-core processor or an octa-core processor. The processor may be implemented using at least one hardware form of DSP (Digital Signal Processing), FPGA (Field Programmable Gate Array), or PLA (Programmable Logic Array). The processor may also include a main processor and coprocessors. The main processor, also known as the CPU (Central Processing Unit), is used to process data in the wake-up state; the coprocessor is a low-power processor used to process data in the standby state. In some embodiments, the processor may integrate a GPU (Graphics Processing Unit), which is responsible for rendering and drawing the content required to be displayed on the screen. In some embodiments, the processor may also include an AI (Artificial Intelligence) processor, which is used to handle computational operations related to machine learning.

[0327] The memory may include one or more computer-readable storage media, which may be non-transitory. The memory may also include high-speed random access memory and non-volatile memory, such as one or more disk storage devices or flash memory devices. In some embodiments, the non-transitory computer-readable storage media in the memory is used to store at least one instruction, at least one program, code set, or instruction set, which is configured to be executed by one or more processors to implement the above-described blood pump pressure information detection method and / or the above-described blood pump control method.

[0328] In some embodiments, the electronic device may also optionally include: a peripheral device interface and at least one peripheral device. The processor, memory, and peripheral device interface can be connected via a bus or signal line. Each peripheral device can be connected to the peripheral device interface via a bus, signal line, or circuit board. Specifically, the peripheral device includes at least one of: radio frequency circuitry, a touch display screen, a camera assembly, an audio circuit, a positioning assembly, and a power supply.

[0329] Those skilled in the art will understand that the above structure does not constitute a limitation on the electronic device, and may include more or fewer components, or combine certain components, or adopt different component arrangements.

[0330] In some possible implementations, the blood pump pressure information detection method described in this application can be implemented in the software of an electronic device. Some particularly suitable hardware electronic device platforms for implementation include microcontrollers, FPGAs, operating system-based microprocessor platforms, or cloud computing platforms. The former allows for faster and more direct access to data, while the latter is more likely to use complex models. It can also be implemented in analog circuits.

[0331] In an exemplary embodiment, a blood pump is also provided, the blood pump including a processor and a memory, the memory storing at least one instruction, at least one program, code set or instruction set, the at least one instruction, the at least one program, the code set or instruction set being loaded and executed by the processor to implement the above-described blood pump pressure information detection method and / or blood pump control method.

[0332] In an exemplary embodiment, a computer-readable storage medium is also provided, the storage medium storing at least one instruction, at least one program, code set, or instruction set, wherein the at least one instruction, the at least one program, the code set, or the instruction set, when executed by a processor, implements the above-described blood pump pressure information detection method and / or blood pump control method.

[0333] Optionally, the computer-readable storage medium may include: ROM (Read Only Memory), RAM (Random Access Memory), SSD (Solid State Drives), or optical disc, etc. The random access memory may include ReRAM (Resistance Random Access Memory) and DRAM (Dynamic Random Access Memory).

[0334] In an exemplary embodiment, a computer program product or computer program is also provided, which includes computer instructions stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium and executes the computer instructions, causing the computer device to perform the aforementioned blood pump pressure information detection method and / or blood pump control method.

[0335] It should be understood that "multiple" as used herein refers to two or more. "And / or" describes the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A alone, A and B simultaneously, or B alone. The character " / " generally indicates that the preceding and following related objects are in an "or" relationship. Furthermore, the step numbers described herein are merely illustrative of one possible execution order. In some other embodiments, the steps may not be executed in numerical order, such as two steps with different numbers being executed simultaneously, or two steps with different numbers being executed in the reverse order of the illustration. This application does not limit this.

[0336] In addition, in the specific embodiments of this application, data such as user information are involved. When the above embodiments of this application are applied to specific products or technologies, user permission or consent is required, and the collection, use and processing of related data must comply with the relevant laws, regulations and standards of the relevant countries and regions.

[0337] The above description is merely an exemplary embodiment of this application and is not intended to limit this application. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the protection scope of this application.

Claims

1. A method for detecting blood pump pressure information, characterized in that, The method includes: During the operation of the blood pump device assisting the target object, the operating signal data of the blood pump device is acquired, and the blood pump device includes a pump head; At least one correction factor corresponding to the target object is obtained; wherein the correction factor characterizes the error between the predicted pressure and the actual pressure corresponding to the pump head; the correction factor is determined when the blood pump device is in a calibration operation state, the calibration operation state including one or more situations in which the actual pressure corresponding to the pump head can be determined, measured or estimated; Based on the at least one correction factor and the operating signal data, the correction pressure data corresponding to the pump head is obtained through conversion processing.

2. The method according to claim 1, characterized in that, The step of obtaining at least one correction factor corresponding to the target object includes: During the calibration operation, a sample of the operating signal data is acquired; The operating signal data samples are converted and processed to obtain the predicted pressure data samples corresponding to the pump head; Identify feature points in the predicted pressure data sample that are associated with one or more of the aforementioned conditions; The correction factor is determined based on the predicted pressure corresponding to the feature point and the actual pressure corresponding to one or more of the situations.

3. The method according to claim 1, characterized in that, The method further includes: The pump speed of the blood pump device is controlled to enter the calibration operation state to meet the conditions for the occurrence of one or more of the above situations; The step of obtaining at least one correction factor corresponding to the target object includes: In the calibration operation state, the at least one calibration factor is determined or updated.

4. The method according to claim 3, characterized in that, The process of controlling the pump speed of the blood pump device to enter the calibration operation state includes: In response to the blood pump start command, the blood pump device is started, and the rotation speed of the blood pump device is controlled to increase to a first target rotation speed; The blood pump device is controlled to operate based on the first target rotational speed; The calibration operating state includes the state in which the blood pump device operates based on the first target rotational speed.

5. The method according to claim 3, characterized in that, The process of controlling the pump speed of the blood pump device to enter the calibration operation state includes: During the operation of the blood pump device, the target speed of the blood pump device is adjusted to the first target speed; The blood pump device is controlled to operate based on the first target rotational speed; The calibration operating state includes the state in which the blood pump device operates based on the first target rotational speed.

6. The method according to claim 5, characterized in that, The step of adjusting the target speed of the blood pump device to a first target speed during operation includes: If a calibration command is received during the operation of the blood pump device, the calibration cycle is reached, or the target parameter in the blood pump device is detected to be abnormal, the target speed of the blood pump device will be adjusted to the first target speed. And / or, during the operation of the blood pump device, a calibration prompt message is issued; in response to a confirmation message for the calibration prompt message, the target speed of the blood pump device is adjusted to the first target speed.

7. The method according to claim 6, characterized in that, The calibration prompt message issued during the operation of the blood pump device includes: The calibration prompt message is issued when the blood pump device reaches the calibration cycle or when the target parameter in the blood pump device is detected to be abnormal. The step of adjusting the target speed of the blood pump device to the first target speed in response to the confirmation information for the calibration prompt includes: In response to a confirmation operation of the calibration prompt information, the target speed of the blood pump device is adjusted to the first target speed.

8. The method according to claim 4 or 5, characterized in that, After determining or updating the at least one correction factor in the correction operation state, the method further includes: The target speed of the blood pump device is adjusted from the first target speed to the second target speed, where the second target speed refers to the target speed set based on the control operation. The blood pump device is controlled to operate based on the second target rotational speed.

9. The method according to claim 1, characterized in that, The conversion processing based on the at least one correction factor and the operating signal data to obtain the corrected pressure data corresponding to the pump head includes: The operating signal data is converted and processed to obtain the predicted pressure data corresponding to the pump head; The predicted pressure data is corrected based on the at least one correction factor to obtain the corrected pressure data.

10. The method according to claim 9, characterized in that, The step of correcting the predicted pressure data based on the at least one correction factor to obtain the corrected pressure data includes: The predicted pressure data is corrected by applying the at least one correction factor to correct the offset error.

11. The method according to claim 1, characterized in that, The conversion processing based on the at least one correction factor and the operating signal data to obtain the corrected pressure data corresponding to the pump head includes: Based on the at least one correction factor, the operating signal data is corrected to obtain corrected operating signal data; The operating signal correction data is converted and processed to obtain the correction pressure data corresponding to the pump head.

12. The method according to claim 11, characterized in that, The step of correcting the operating signal data based on the at least one correction factor to obtain corrected operating signal data includes: The offset error is corrected by applying the at least one correction factor to the operating signal data to obtain the corrected operating signal data.

13. The method according to claim 1, characterized in that, The method further includes: A pump head pressure prediction model is obtained, which characterizes the conversion relationship between the operating signal of the blood pump device and the pump head pressure. The conversion processing based on the at least one correction factor and the operating signal data to obtain the corrected pressure data corresponding to the pump head includes: The operating signal data is input into the pump head pressure prediction model for conversion processing, and the predicted pressure data corresponding to the pump head is output; the predicted pressure data is corrected based on the at least one correction factor to obtain the corrected pressure data; Alternatively, the operating signal data can be corrected based on the at least one correction factor to obtain corrected operating signal data; the corrected operating signal data can be input into the pump head pressure prediction model for conversion processing to output the corrected pressure data. Alternatively, based on the at least one correction factor, the pump head pressure prediction model is corrected to obtain a corrected pump head pressure prediction model; the operating signal data is input into the corrected pump head pressure prediction model for conversion processing, and the corrected pressure data is output.

14. The method according to claim 13, characterized in that, The pump head pressure prediction model is obtained by adjusting the parameters of the original pump head pressure prediction model based on hydraulic test results.

15. The method according to claim 13, characterized in that, The pump head pressure prediction model includes: Acquire operational signal test data samples and pump head pressure detection data samples corresponding to the operational signal test data samples; Based on the operating signal test data sample and the pump head pressure detection data sample, the pump head pressure prediction model is generated; The pump head pressure prediction model includes at least one of the following: Linear relational models, non-linear relational models, lookup tables, and machine learning models.

16. The method according to claim 1, characterized in that, The acquisition of the operating signal data of the blood pump device includes: Obtain the raw data of the running signals; The raw data is subjected to signal processing to obtain the running signal data; wherein the signal processing method includes at least one of the following: Based on low-pass filter filtering; Based on bandpass filter filtering; Determine the average value of the operating signal data over a fixed time period; Determine the average value of the operating signal data over the target number of heartbeat cycles; Determine the root mean square value of the operating signal data within a fixed time period; Determine the root mean square value of the operating signal data over the target number of heartbeat cycles; Determine the basic values ​​of the operating signal data within a fixed time period; Determine the basic value of the operating signal data over the target number of heartbeat cycles.

17. The method according to claim 1, characterized in that, The method further includes at least one of the following steps: Determine the average net pressure corresponding to the corrected pressure data over a fixed time period; Determine the average net pressure corresponding to the corrected pressure data over the target number of heartbeat cycles; Determine the root mean square net pressure value corresponding to the corrected pressure data over a fixed time period; Determine the root mean square net pressure value of the corrected pressure data for the target number of heartbeat cycles; Determine the amplitude of the net pressure fundamental frequency component corresponding to the corrected pressure data over a fixed time period; Determine the amplitude of the net pressure fundamental frequency component corresponding to the target number of heartbeat cycles of the corrected pressure data; Determine the net pressure waveform spectrum corresponding to the corrected pressure data.

18. The method according to claim 1, characterized in that, The method further includes at least one of the following steps: Display the calibration pressure data; An alarm message is triggered based on the corrected pressure data; Based on the corrected pressure data and aortic pressure data, left ventricular pressure data is determined, wherein the aortic pressure data is obtained from the detection module corresponding to the blood pump device; The calibration pressure data is converted to obtain the pump flow indication data corresponding to the blood pump device; Based on the corrected pressure data, pump position indication information is determined.

19. The method according to any one of claims 1-18, characterized in that, The at least one correction factor includes at least one of the following: The operating signal correction factor, the conversion relationship correction factor, and the pressure data correction factor are defined as follows: the operating signal correction factor represents the correction factor corresponding to the operating signal data; the conversion relationship correction factor represents the correction factor corresponding to the conversion relationship between the operating signal data and the predicted pressure data; the predicted pressure data is the predicted pressure obtained by converting the operating signal data based on the conversion relationship; and the pressure data correction factor represents the correction factor corresponding to the predicted pressure data. The at least one correction factor includes at least one of the following: Offset value, scaling factor.

20. The method according to claim 19, characterized in that, The pressure data correction factor includes at least one of a fixed pressure offset value and a speed-related pressure offset value, wherein the pressure offset value characterizes the offset error between the predicted pressure and the actual pressure corresponding to the pump head. The operating signal correction factor includes at least one of a fixed current offset value and a speed-related current offset value; The scaling factor includes at least one of a fixed scaling factor and a speed-related scaling factor.

21. The method according to any one of claims 1-18, characterized in that, The operating signal data includes the rotation speed signal data corresponding to the blood pump device, and the rotation speed signal data includes at least one of the following: motor rotation speed data, impeller rotation speed data, rotation speed error data, and coupling rotation speed difference data; The speed error data refers to the error data between the target speed and the actual speed, and the coupled speed difference data refers to the speed difference data between the coupled drive components in the blood pump device.

22. The method according to any one of claims 1-18, characterized in that, The operating signal data includes torque sensing data.

23. The method according to any one of claims 1-18, characterized in that, The operating signal data includes current data, and the current data includes at least one of the following: Motor controller current data, motor current.

24. The method according to claim 23, characterized in that, The motor controller current data includes at least one of the following: The net output current of the motor controller; The proportional term current corresponding to the PID control module; the motor controller includes a PID control module. Current data determined based on the proportional term current and derivative term current corresponding to the PID control module; The current data is determined based on the proportional term current and integral term current corresponding to the PID control module.

25. The method according to claim 23, characterized in that, The motor current includes at least one of the following: The current in at least one motor winding of the motor; The average current corresponding to at least two motor windings; The orthogonal axis current is determined based on the motor winding current, wherein the motor winding current is obtained based on the motor position transformation.

26. The method according to any one of claims 1-18, characterized in that, The corrected pressure data includes the corrected net pump head pressure data, and the one or more cases include at least one of the following: The opening of the aortic valve during a cardiac cycle; The pump head net pressure is based on measurements from a net pressure sensor. The inlet and outlet pressures of the pump head are based on measurements from pressure sensors; One of the pump head's inlet pressure and outlet pressure is measured by a sensor, while the other is determined or estimated based on physiological effects.

27. The method according to claim 1, characterized in that, The method further includes: Obtain the blood viscosity data of the target object; The conversion processing based on the at least one correction factor and the operating signal data to obtain the corrected pressure data corresponding to the pump head includes: Based on the at least one correction factor, the blood viscosity data, and the operating signal data, the correction pressure data corresponding to the pump head is obtained through conversion processing.

28. The method according to claim 27, characterized in that, The conversion processing based on the at least one correction factor, the blood viscosity data, and the operating signal data to obtain the correction pressure data corresponding to the pump head includes: Based on the blood viscosity data, the model parameters of the pump head pressure prediction model are adjusted to obtain a pump head pressure prediction model that matches the current blood viscosity. The pump head pressure prediction model represents the conversion relationship between the operating signal of the blood pump device and the pump head pressure. Based on the adjusted pump head pressure prediction model, at least one correction factor and the operating signal data are converted to obtain the above-mentioned corrected pressure data.

29. The method according to claim 1, characterized in that, The blood pump device includes a pressure sensor, and the operating modes corresponding to the pressure sensor include an operating mode and a shutdown mode. In the shutdown mode, the step of performing conversion processing based on the at least one correction factor and the operating signal data to obtain the correction pressure data corresponding to the pump head is executed.

30. A blood pump pressure information detection device, characterized in that, The device includes: The data acquisition module is used to acquire the operating signal data of the blood pump device during the operation of the blood pump device assisting the target object. The blood pump device includes a pump head. A correction factor acquisition module is used to acquire at least one correction factor corresponding to the target object; wherein the correction factor characterizes the error between the predicted pressure and the actual pressure corresponding to the pump head; the correction factor is determined when the blood pump device is in a calibration operation state, the calibration operation state including one or more situations in which the actual pressure corresponding to the pump head can be determined, measured or estimated; The pressure conversion and correction module is used to perform conversion processing based on the at least one correction factor and the operating signal data to obtain the corrected pressure data corresponding to the pump head.

31. An electronic device, characterized in that, The electronic device includes a processor and a memory, wherein the memory stores at least one instruction, at least one program, code set, or instruction set, and the at least one instruction, the at least one program, the code set, or the instruction set is loaded and executed by the processor to implement the blood pump pressure information detection method as described in any one of claims 1 to 29.

32. A blood pump, characterized in that, The blood pump includes a processor and a memory, wherein the memory stores at least one instruction, at least one program, a code set, or an instruction set, and the at least one instruction, the at least one program, the code set, or the instruction set is loaded and executed by the processor to implement the blood pump pressure information detection method as described in any one of claims 1 to 29.

33. A computer-readable storage medium, characterized in that, The storage medium stores at least one instruction, at least one program, code set, or instruction set, wherein the at least one instruction, the at least one program, the code set, or instruction set is loaded and executed by a processor to implement the blood pump pressure information detection method as described in any one of claims 1 to 29.

34. A computer program product, characterized in that, The computer program product includes computer instructions stored in a computer-readable storage medium. The processor of the computer device reads the computer instructions from a computer-readable storage medium, and the processor executes the computer instructions to cause the computer device to perform the blood pump pressure information detection method as described in any one of claims 1 to 29.

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