A radial artery compression pressure determination method, apparatus, electronic device, and medium

Abstract

A radial artery compression pressure determination method, device, electronic equipment and medium are provided, relating to the field of medical devices. In the method, basic compression pressure data and blood flow data measured by a sensor are obtained; in the automatic adjustment mode, an initial compression pressure is determined based on a preset PID control algorithm according to the basic compression pressure data and the blood flow data; it is monitored whether a remote intervention request signal sent by a remote monitoring terminal is received; when the remote intervention request signal is received, the automatic adjustment mode is switched to a remote intervention mode; in the remote intervention mode, a remote adjustment instruction sent by the remote monitoring terminal is received, and the remote adjustment instruction includes a target compression pressure value or a pressure adjustment amount; and the target compression pressure is calculated according to the remote adjustment instruction in combination with the initial compression pressure. The technical solution provided in the application improves the flexibility of pressure force control.

Description

Technical Field

[0001] This application relates to the field of medical devices, specifically to a method, device, electronic device, and medium for determining radial artery compression pressure. Background Technology

[0002] With the continuous development of medical technology and the popularization of minimally invasive interventional concepts, cardiac interventional surgery via the radial artery approach has been widely used worldwide due to its significant advantages such as minimal trauma, rapid patient recovery, fewer complications, and shorter hospital stays, and is gradually becoming the preferred route for cardiovascular interventional treatment. After a successful procedure, timely and effective compression hemostasis at the radial artery puncture site is a crucial step in ensuring surgical success and preventing postoperative complications, directly affecting the patient's prognosis and recovery quality.

[0003] Currently, clinical practice mainly relies on manual or mechanical compression. However, this method is highly dependent on operator experience, and inaccurate pressure control can easily lead to complications such as radial artery occlusion or incomplete hemostasis. In addition, most existing equipment allows for local manual adjustment of compression pressure. Therefore, existing radial artery compression hemostasis methods often lack a mechanism to adjust according to the patient's real-time condition after setting the initial pressure, resulting in inflexible pressure control. Summary of the Invention

[0004] This application provides a method, device, electronic device, and medium for determining radial artery compression pressure, which improves the flexibility of pressure control.

[0005] A first aspect of this application provides a method for determining radial artery compression pressure. The method includes: acquiring baseline compression pressure data and blood flow data measured by a sensor; determining an initial compression pressure based on the baseline compression pressure data and the blood flow data using a preset PID control algorithm in an automatic adjustment mode; monitoring whether a remote intervention request signal sent by a remote monitoring terminal is received; switching the automatic adjustment mode to a remote intervention mode when the remote intervention request signal is received; receiving a remote adjustment command sent by the remote monitoring terminal in the remote intervention mode, the remote adjustment command including a target compression pressure value or a pressure adjustment amount; and calculating the target compression pressure based on the remote adjustment command and the initial compression pressure.

[0006] By employing the above technical solution, baseline compression pressure data and blood flow data measured by sensors are acquired, enabling real-time acquisition of pressure and blood flow status information during radial artery compression, providing a data foundation for subsequent pressure control. In automatic adjustment mode, the initial compression pressure is determined based on the baseline compression pressure data and blood flow data using a preset PID control algorithm, achieving automated adjustment of the compression pressure and reducing the frequency of manual intervention. By monitoring whether a remote intervention request signal is received from the remote monitoring terminal, the remote control needs of medical personnel can be responded to promptly. When a remote intervention request signal is received, the automatic adjustment mode is switched to the remote intervention mode, realizing flexible switching between automatic control and remote manual control. In remote intervention mode, remote adjustment instructions are received, and the target compression pressure is calculated based on these instructions and the initial compression pressure, allowing medical personnel to remotely adjust the compression pressure parameters according to the actual situation, improving the flexibility and controllability of compression pressure determination. This technical solution, by introducing sensor data acquisition, PID control algorithms, and remote monitoring and intervention functions, achieves accurate determination and dynamic adjustment of radial artery compression pressure, overcoming the limitations of traditional methods such as inaccurate pressure control, lack of real-time adjustment, and lack of remote operation. The technical benefits include improved safety and effectiveness of compression hemostasis, reduced risk of complications, reduced reliance on manual experience, and improved operational efficiency and patient recovery quality.

[0007] Optionally, determining the initial compression pressure based on the preset PID control algorithm, according to the baseline compression pressure data and the blood flow data, specifically includes: extracting blood flow velocity feature values ​​and vascular pulsation frequency feature values ​​from the blood flow data, comparing the blood flow velocity feature values ​​with a preset blood flow threshold to generate a blood flow deviation signal; inputting the baseline compression pressure data into the proportional component of the preset PID control algorithm to calculate a proportional adjustment amount proportional to the current compression pressure, and inputting the blood flow deviation signal into the integral component of the preset PID control algorithm to perform time integration on the blood flow deviation signal to generate an integral adjustment amount; calculating the differential adjustment amount through the derivative component of the preset PID control algorithm based on the rate of change of the vascular pulsation frequency feature values; weighting and fusing the proportional adjustment amount, the integral adjustment amount, and the differential adjustment amount to obtain a PID comprehensive adjustment output value, and determining the initial compression pressure based on the PID comprehensive adjustment output value.

[0008] By employing the above technical solution, blood flow velocity and vascular pulsation frequency feature values ​​are extracted from blood flow data, enabling the acquisition of key characteristic parameters representing the blood flow state. Comparing the blood flow velocity feature values ​​with a preset blood flow threshold generates a blood flow deviation signal, quantifying the degree of deviation between the current and target blood flow states. Inputting baseline compression pressure data into a proportional loop calculates the proportional adjustment, achieving rapid response adjustment proportional to the current compression pressure. Inputting the blood flow deviation signal into an integral loop performs time integration to generate an integral adjustment, eliminating steady-state errors in blood flow deviation. Based on the rate of change of vascular pulsation frequency feature values, a differential adjustment is calculated through a derivative loop, enabling predictive adjustment of rapid changes in blood flow state. Weighted fusion of the proportional, integral, and differential adjustment values ​​yields a PID comprehensive adjustment output value, achieving comprehensive decision-making for multi-dimensional adjustment quantities. The determined initial compression pressure balances response speed, steady-state accuracy, and dynamic prediction capability.

[0009] Optionally, the step of extracting blood flow velocity feature values ​​and vascular pulsation frequency feature values ​​based on the blood flow data specifically includes: constructing a blood flow velocity time-series curve based on the blood flow data; performing peak detection on the blood flow velocity time-series curve to identify the peak blood flow velocity points within each cardiac cycle, and calculating the average value of all blood flow velocity peak points within a preset time window as the blood flow velocity feature value; performing periodic analysis on the blood flow velocity time-series curve, using the autocorrelation function method to identify the time interval between adjacent pulsation cycles, and calculating the reciprocal of the time interval as the instantaneous pulsation frequency; and performing a moving average filter on multiple instantaneous pulsation frequencies within the preset time window to obtain the vascular pulsation frequency feature value.

[0010] By employing the above technical solutions, a blood flow velocity time-series curve is constructed based on blood flow data, transforming discrete blood flow data into a continuous time-series representation, facilitating subsequent feature extraction and processing. Peak detection of the blood flow velocity time-series curve identifies the peak points of blood flow velocity within each cardiac cycle, accurately pinpointing the extreme moments of blood flow velocity. The average value of all blood flow velocity peak points within a preset time window is calculated as the blood flow velocity feature value; multi-cycle averaging reduces the impact of fluctuations in single measurements, improving the stability of the blood flow velocity feature value. Periodic analysis of the blood flow velocity time-series curve and the use of the autocorrelation function method to identify the time interval between adjacent pulsation cycles accurately identify the pulsation cycle pattern of blood vessels. The reciprocal of the time interval is calculated as the instantaneous pulsation frequency, realizing the conversion from time-domain parameters to frequency parameters. A moving average filter is applied to multiple instantaneous pulsation frequencies within the preset time window to obtain the vascular pulsation frequency feature value, smoothing frequency fluctuations and obtaining stable and reliable vascular pulsation frequency feature values.

[0011] Optionally, before determining the initial compression pressure based on the baseline compression pressure data and the blood flow data using a preset PID control algorithm, the method further includes: acquiring the patient's baseline physiological parameters, including the patient's age, weight, baseline blood pressure, and coagulation function indicators; matching a corresponding PID control parameter group from a preset parameter configuration library based on the baseline physiological parameters, the PID control parameter group including a proportional gain, integral time constant, and derivative time constant; and loading the PID control parameter group into the preset PID control algorithm to complete the personalized parameter initialization of the preset PID control algorithm.

[0012] By employing the above technical solution, basic physiological parameters of patients are obtained, including patient age, weight, baseline blood pressure, and coagulation function indicators. This allows for the acquisition of individualized physiological characteristic data related to compression pressure control. Based on these basic physiological parameters, corresponding PID control parameter sets are matched from a preset parameter configuration library. This enables the selection of suitable control parameters according to the physiological characteristics of different patients, avoiding control effect deviations caused by using uniform, fixed parameters. The PID control parameter set includes proportional gain, integral time constant, and derivative time constant, covering the core parameters of the PID control algorithm. Loading the PID control parameter set into the preset PID control algorithm completes personalized parameter initialization, allowing the PID control algorithm to be personalized for the physiological characteristics of different patients, improving the targeting and adaptability of initial compression pressure determination.

[0013] Optionally, the step of calculating the target compression pressure based on the remote adjustment command and the initial compression pressure specifically includes: parsing the remote adjustment command and determining whether the type of the remote adjustment command is a target compression pressure value type or a pressure adjustment amount type; when the type of the remote adjustment command is the target compression pressure value type, extracting the target compression pressure value carried in the remote adjustment command, calculating the difference between the target compression pressure value and the initial compression pressure to obtain a pressure difference value, and converting the pressure difference value into a force adjustment increment according to a preset pressure conversion coefficient; when the type of the remote adjustment command is the pressure adjustment amount type, extracting the pressure adjustment amount carried in the remote adjustment command, determining the force adjustment direction according to the positive or negative sign of the pressure adjustment amount, where a positive value indicates the pressure increase direction and a negative value indicates the pressure decrease direction; calculating the target compression pressure based on the force adjustment increment or the pressure adjustment amount, combined with the initial compression pressure and the force adjustment direction, through linear superposition operation; performing a safety threshold check on the target compression pressure, and when the target compression pressure exceeds a preset safety threshold range, correcting the target compression pressure to the upper limit of the preset safety threshold range.

[0014] By employing the above technical solution, remote adjustment commands are parsed and their type (target pressure value or pressure adjustment amount) is determined, enabling the identification of different forms of remote control commands and supporting multiple command input methods. When the remote adjustment command is a target pressure value type, the target pressure value is extracted and its difference from the initial pressure is calculated to obtain the pressure difference. This difference is then converted into a force adjustment increment based on a preset pressure conversion coefficient, realizing the conversion from absolute pressure value to relative adjustment amount. When the remote adjustment command is a pressure adjustment amount type, the pressure adjustment amount is extracted, and the force adjustment direction is determined based on the positive or negative sign, directly obtaining relative adjustment parameters and adjustment direction information. Based on the force adjustment increment or pressure adjustment amount, the target pressure is calculated through linear superposition of the initial pressure and the force adjustment direction, achieving comprehensive calculation of multiple parameters. A safety threshold check is performed on the target pressure, and correction is applied to the upper limit if it exceeds the preset safety threshold range, preventing the target pressure from exceeding the safe range and ensuring the safety of pressure output.

[0015] Optionally, after calculating the target compression pressure according to the remote adjustment command and in conjunction with the initial compression pressure, the method further includes: constructing a vascular compliance model of the patient's radial artery based on the blood flow data, wherein the vascular compliance model is used to characterize the nonlinear mapping relationship between the deformation characteristics of the radial artery under different compression pressures and the degree of blood flow obstruction; calculating the vascular wall stress distribution characteristics under the target compression pressure according to the vascular compliance model, and identifying stress concentration areas in the vascular wall stress distribution characteristics, wherein the stress concentration areas are potential tissue damage risk areas; performing pressure compensation or pressure reduction based on the location information and stress peak value of the stress concentration areas, generating a target pressure distribution matrix, and sending the target pressure distribution matrix to the compression component.

[0016] By employing the aforementioned technical solution, a vascular compliance model of the radial artery is constructed based on blood flow data. This model establishes a nonlinear mapping relationship between the deformation characteristics of the radial artery under different compression pressures and the degree of blood flow obstruction, providing a model foundation for subsequent stress analysis. The stress distribution characteristics of the vessel wall under the target compression pressure are calculated based on the vascular compliance model, enabling the acquisition of the stress state at various locations on the vessel wall under compression. Stress concentration areas within the vessel wall stress distribution characteristics are identified as potential tissue damage risk areas, allowing for the location of high-risk areas that may cause tissue damage. Pressure compensation or reduction is performed based on the location information and peak stress of the stress concentration areas, enabling differentiated pressure adjustments for different regions. A target pressure distribution matrix is ​​generated and sent to the compression component, expanding from a single pressure value to a spatially distributed pressure matrix, allowing the compression component to perform refined zoned pressure control.

[0017] Optionally, the step of performing pressure compensation or pressure reduction based on the location information and peak stress of the stress concentration area to generate a target pressure distribution matrix specifically includes: mapping the operating area of ​​the compression component to a two-dimensional compression matrix composed of multiple compression units based on preset structural parameters of the compression component; projecting the location information of the stress concentration area onto the two-dimensional compression matrix to obtain a central compression unit group; calculating the pressure reduction amount for the central compression unit group based on the difference between the peak stress and a preset safe stress threshold; applying a preset pressure distribution function based on the pressure reduction amount to generate a pressure attenuation value for each compression unit in the central compression unit group; allocating the pressure reduction amount, with a weight inversely proportional to the distance from the central compression unit group, to the peripheral compression units in the two-dimensional compression matrix other than the central compression unit group, and calculating a pressure compensation value for each peripheral compression unit; algebraically superimposing the target compression pressure of each compression unit in the two-dimensional compression matrix with the corresponding pressure attenuation value or pressure compensation value to generate a target pressure distribution matrix, and sending the target pressure distribution matrix to the compression component.

[0018] By adopting the above technical solution, the operating area is mapped into a two-dimensional compression matrix composed of multiple compression units based on the preset structural parameters of the compression component, thus establishing a spatial mapping relationship between the compression component and pressure control. Projecting the location information of the stress concentration area onto the two-dimensional compression matrix yields the central compression unit group, allowing for the identification of the target unit area requiring pressure reduction. Calculating the pressure reduction amount for the central compression unit group based on the difference between the peak stress and the preset safe stress threshold quantifies the magnitude of pressure reduction. Applying a preset pressure distribution function based on the pressure reduction amount generates a pressure attenuation value for each compression unit within the central compression unit group, achieving distributed pressure attenuation within the central area. Distributing the pressure reduction amount to surrounding compression units with a weight inversely proportional to the distance from the central compression unit group to calculate pressure compensation values ​​allows for the reasonable distribution of reduced pressure to the surrounding areas. Algebraically superimposing the target compression pressure of each compression unit with the corresponding pressure attenuation value or pressure compensation value generates a target pressure distribution matrix, achieving spatial redistribution of pressure. This maintains the overall compression effect while reducing local pressure in stress concentration areas.

[0019] A second aspect of this application provides a radial artery compression pressure determination device, the device comprising a data acquisition module, an automatic adjustment module, a monitoring module, a mode adjustment module, a remote intervention module, and a pressure determination module, wherein: the data acquisition module is used to acquire baseline compression pressure data and blood flow data measured by sensors; the automatic adjustment module is used to determine an initial compression pressure based on the baseline compression pressure data and the blood flow data in automatic adjustment mode, based on a preset PID control algorithm; the monitoring module is used to monitor whether a remote intervention request signal sent by a remote monitoring terminal is received; the mode adjustment module is used to switch the automatic adjustment mode to a remote intervention mode when the remote intervention request signal is received; the remote intervention module is used to receive a remote adjustment command sent by the remote monitoring terminal in the remote intervention mode, the remote adjustment command including a target compression pressure value or a pressure adjustment amount; and the pressure determination module is used to calculate the target compression pressure based on the remote adjustment command and the initial compression pressure.

[0020] A third aspect of this application provides an electronic device including a processor, a memory, a user interface, and a network interface, wherein the memory is used to store instructions, the user interface and the network interface are both used to communicate with other devices, and the processor is used to execute the instructions stored in the memory to cause the electronic device to perform the method as described in any of the foregoing.

[0021] A fourth aspect of this application provides a computer-readable storage medium storing instructions that, when executed, perform the method described in any of the preceding descriptions.

[0022] In summary, one or more technical solutions provided in this application have at least the following technical effects or advantages:

[0023] 1. By introducing sensor measurement data, PID control algorithm and blood flow characteristic analysis, this technical solution can accurately extract blood flow velocity characteristic value and vascular pulsation frequency characteristic value, dynamically adjust the compression pressure of the radial artery, and ensure that the pressure is always within a safe and effective range, thereby avoiding problems such as radial artery occlusion, incomplete hemostasis or tissue damage caused by improper pressure control in traditional methods.

[0024] 2. This technical solution combines the patient's basic physiological parameters with the matching of PID control parameter sets and the construction of a vascular compliance model to adapt to individual patient differences, enhancing the personalized control capability of the equipment. Simultaneously, stress distribution analysis and pressure matrix optimization further improve the uniformity and safety of the compression pressure distribution, reducing the risk of postoperative complications.

[0025] 3. This technical solution supports remote monitoring and adjustment. Medical staff can adjust the target compression pressure in real time via remote commands and dynamically optimize the pressure distribution of the compression components based on blood flow data, improving the flexibility and reliability of the equipment. This function not only enhances the applicability in telemedicine scenarios but also effectively reduces the workload of medical staff while ensuring the quality of postoperative recovery for patients. Attached Figure Description

[0026] Figure 1 This is a flowchart illustrating a method for determining radial artery compression pressure disclosed in an embodiment of this application;

[0027] Figure 2 This is another schematic flowchart of a method for determining radial artery compression pressure disclosed in an embodiment of this application;

[0028] Figure 3 This is a schematic diagram of a radial artery compression pressure determination device provided in an embodiment of this application;

[0029] Figure 4 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application.

[0030] Explanation of reference numerals in the attached drawings: 301, Data acquisition module; 302, Automatic adjustment module; 303, Monitoring module; 304, Mode adjustment module; 305, Remote intervention module; 306, Pressure determination module; 400, Electronic device; 401, Processor; 402, Communication bus; 403, User interface; 404, Network interface; 405, Memory. Detailed Implementation

[0031] To enable those skilled in the art to better understand the technical solutions in this specification, the technical solutions in the embodiments of this specification will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments.

[0032] In the description of the embodiments of this application, the words "for example" or "for instance" are used to indicate examples, illustrations, or explanations. Any embodiment or design that is described as "for example" or "for instance" in the embodiments of this application should not be construed as being more preferred or advantageous than other embodiments or design options. Rather, the use of the words "for example" or "for instance" is intended to present the relevant concepts in a specific manner.

[0033] In the description of the embodiments of this application, the term "multiple" means two or more. For example, multiple system devices refer to two or more system devices, and multiple screen terminals refer to two or more screen terminals. Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the indicated technical features. Thus, a feature defined with "first" or "second" may explicitly or implicitly include one or more of that feature. The terms "comprising," "including," "having," and variations thereof all mean "including but not limited to," unless otherwise specifically emphasized.

[0034] This application provides a method for determining radial artery compression pressure, referring to... Figure 1 , Figure 1 This is a flowchart illustrating a method for determining radial artery compression pressure according to an embodiment of this application. The method is applied to a device, which is a controller for a radial artery compression hemostat. The controller can execute a radial artery compression pressure determination procedure. The method includes steps S101 to S106, as follows:

[0035] Step S101: Acquire the baseline compression pressure data and blood flow data measured by the sensor.

[0036] In step S101, the sensor refers to a hardware device installed on the radial artery compression hemostat for real-time monitoring of physical quantities. The baseline compression pressure data refers to the sequence of pressure values ​​directly applied to the patient's radial artery, collected by the pressure sensor. The blood flow data refers to the signal sequence characterizing the blood flow state within the radial artery, collected by the blood flow sensor.

[0037] Specifically, the controller continuously receives data from pressure and blood flow sensors electrically connected to it via a built-in data acquisition interface at a preset sampling frequency, such as 100 times per second. The pressure sensor, such as a piezoresistive thin-film sensor, converts the sensed physical pressure into a voltage or current signal, which is then converted into digitized baseline compression pressure data by an analog-to-digital converter within the controller. The blood flow sensor, such as an ultrasonic Doppler sensor, detects blood flow velocity and direction by emitting and receiving ultrasonic waves, and processes the results into digitized blood flow data. The controller stores the acquired baseline compression pressure data and blood flow data in an internal buffer for later retrieval in subsequent steps.

[0038] Step S102: In automatic adjustment mode, based on the preset PID control algorithm, the initial compression pressure is determined according to the baseline compression pressure data and blood flow data.

[0039] In step S102, the automatic adjustment mode refers to the controller's autonomous operation based on a preset algorithm and real-time sensor data, requiring no manual intervention. The preset PID control algorithm is a closed-loop control algorithm combining proportional, integral, and derivative adjustment mechanisms, used to ensure the system output quickly and stably reaches the desired value. The initial compression pressure refers to a reference pressure value calculated by the controller using the algorithm in automatic adjustment mode, which is sufficient to initially achieve effective hemostasis and ensure unobstructed blood flow to the distal end.

[0040] Specifically, after the controller enters the automatic adjustment mode, it activates its internal preset PID control algorithm program. The controller uses the real-time blood flow data acquired in step S101 as input, analyzing the blood flow data to determine whether the current hemostasis state has reached the preset target, such as maintaining the distal blood flow velocity above a safe threshold. Simultaneously, the controller uses the baseline compression pressure data as a feedback signal. The preset PID control algorithm performs proportional, integral, and derivative calculations based on the deviation between the blood flow state and the target, as well as the changing trend of the baseline compression pressure, to generate an adjustment signal. This adjustment signal drives the actuator of the compression device, such as a miniature air pump or motor, to adjust the applied pressure until the baseline compression pressure data and blood flow data reach a dynamic equilibrium. At this point, the controller records the pressure value in this stable state as the initial compression pressure.

[0041] In one possible implementation, before determining the initial compression pressure based on baseline compression pressure data and blood flow data using a preset PID control algorithm, the method further includes: acquiring the patient's baseline physiological parameters, including the patient's age, weight, baseline blood pressure, and coagulation function indicators; matching the corresponding PID control parameter set from a preset parameter configuration library based on the baseline physiological parameters, the PID control parameter set including proportional coefficient, integral time constant, and derivative time constant; and loading the PID control parameter set into the preset PID control algorithm to complete the personalized parameter initialization of the preset PID control algorithm.

[0042] Basic physiological parameters refer to a set of key data reflecting the individual physiological characteristics of a patient. Patient age refers to the patient's actual age in years. Weight refers to the patient's body mass. Baseline blood pressure refers to the patient's normal blood pressure level under non-stress conditions. Coagulation function indicators refer to medical test data used to assess the patient's blood clotting ability, such as prothrombin time or activated partial thromboplastin time. The preset parameter configuration library is a structured database stored in the controller's memory, pre-storing multiple sets of PID control parameters for different physiological characteristics of different populations. A PID control parameter set is a specific combination of three core parameters: proportional gain, integral time constant, and derivative time constant. This combination determines the response speed, stability, and anti-interference capability of the PID control algorithm. The proportional gain is used to adjust the controller's response strength to the current error. The integral time constant is used to adjust the speed at which the controller eliminates the system's steady-state error. The derivative time constant is used to adjust the controller's ability to predict and suppress error trends. Personalized parameter initialization refers to configuring the PID control parameter set selected for a specific patient into the algorithm, so that subsequent calculations of the algorithm are based on the patient's individual characteristics.

[0043] Specifically, before activating the automatic adjustment mode, the controller prompts the operator to input the patient's basic physiological parameters through its human-machine interface, such as a touch screen. Alternatively, the controller receives basic physiological parameters confirmed and issued by medical staff from a remote monitoring terminal that is synchronized with the hospital's information system via a wireless communication interface. After receiving the data, the controller verifies the data format and range, such as checking whether the age and weight are within a reasonable range, and then stores the verified basic physiological parameters in a designated internal storage unit.

[0044] Next, the controller invokes a built-in matching algorithm program. This program takes the basic physiological parameter information obtained in the previous steps as input. The algorithm contains a set of preset matching rules or decision tree models. For example, the rule might be defined as: if the patient is over 70 years old and coagulation function indicators show coagulation delay, then match the parameter set with a high proportional gain and long integral time for more conservative and stable pressure regulation. The controller comprehensively evaluates the patient's basic physiological parameter information based on these rules, and then searches and locks the uniquely corresponding PID control parameter set in the preset parameter configuration library.

[0045] Then, after successfully matching the PID control parameter set, the controller reads the values ​​of the proportional coefficient, integral time constant, and derivative time constant contained in that parameter set from the preset parameter configuration library. Subsequently, the controller writes these three values ​​into the corresponding parameter variable addresses within the preset PID control algorithm program, overwriting the algorithm's default or previously used parameter values. After this operation, the operating characteristics of the preset PID control algorithm are customized to adapt to the current patient's physiological condition, and the entire personalized parameter initialization process is complete. The controller can then use this initialized algorithm to execute subsequent automatic pressure regulation tasks.

[0046] In one possible implementation, the initial compression pressure is determined based on a preset PID control algorithm, according to the baseline compression pressure data and blood flow data. Specifically, this includes steps S1021-S1024, as follows:

[0047] Step S1021: Based on the blood flow data, extract the blood flow velocity feature value and the vascular pulsation frequency feature value, compare the blood flow velocity feature value with the preset blood flow threshold to generate a blood flow deviation signal, and compare the blood flow velocity feature value with the preset blood flow threshold to generate a blood flow deviation signal.

[0048] In step S1021, blood flow data refers to the raw signal or data stream reflecting blood flow within the radial artery, acquired by a sensor; blood flow velocity characteristic value represents a specific value extracted from the blood flow data that quantifies the speed of blood flow; vascular pulsation frequency characteristic value represents a frequency value extracted from the blood flow data that reflects the speed of heart rate or periodic pulsation of blood vessels; the preset blood flow threshold is the minimum acceptable blood flow velocity characteristic value preset to ensure the safety of the distal limb and avoid ischemia and necrosis. The blood flow deviation signal refers to the difference between the actually measured blood flow velocity characteristic value and the preset blood flow threshold, and this signal is used to drive the PID control algorithm for adjustment.

[0049] Specifically, the controller first receives real-time blood flow data collected by monitoring devices such as an ultrasound Doppler sensor deployed at the patient's radial artery. Next, the controller performs signal processing on the received blood flow data, for example, using Fast Fourier Transform or peak detection algorithms to calculate and extract blood flow velocity feature values ​​representing the current blood flow state, as well as vascular pulsation frequency feature values ​​reflecting the patient's heart rate, from the waveform of the blood flow data. After feature extraction, the controller reads a pre-set, clinically significant lower limit of blood flow velocity, such as 20 cm / s, from its internal memory as a preset blood flow threshold. The controller subtracts the calculated blood flow velocity feature value from this preset blood flow threshold; the difference is the blood flow deviation signal. If the blood flow velocity feature value is lower than the preset blood flow threshold, the blood flow deviation signal is negative, indicating that the compression pressure needs to be reduced.

[0050] In one possible implementation, blood flow velocity feature values ​​and vascular pulsation frequency feature values ​​are extracted based on blood flow data. Specifically, this includes: constructing a blood flow velocity time-series curve based on blood flow data; performing peak detection on the blood flow velocity time-series curve to identify the peak blood flow velocity points within each cardiac cycle, and calculating the average value of all blood flow velocity peak points within a preset time window as the blood flow velocity feature value; performing periodic analysis on the blood flow velocity time-series curve, using the autocorrelation function method to identify the time interval between adjacent pulsation cycles, and calculating the reciprocal of the time interval as the instantaneous pulsation frequency; and performing a moving average filter on multiple instantaneous pulsation frequencies within the preset time window to obtain the vascular pulsation frequency feature value.

[0051] A blood flow velocity time-series curve is a two-dimensional graph formed by arranging continuously acquired blood flow data in chronological order, with time as the x-axis and blood flow velocity as the y-axis. Peak detection refers to the algorithmic process of automatically identifying and locating local maxima on the blood flow velocity time-series curve. A cardiac cycle refers to the entire process of the heart completing one contraction and relaxation, which is represented as a complete pulsating waveform on the blood flow velocity time-series curve. The blood flow velocity peak point is the point where the blood flow velocity reaches its maximum value within a cardiac cycle. A preset time window is a fixed duration set for statistical calculations, such as 5 seconds. Blood flow velocity characteristic values ​​are representative values ​​that quantify the blood flow state within a preset time window. Period analysis is a signal processing technique used to extract the periodic characteristics of a signal. The autocorrelation function method is a mathematical method that determines the main period of a signal by calculating the similarity between the signal and itself at different time delays. The time interval of a pulsating cycle is the time difference between two adjacent blood flow velocity peak points on the blood flow velocity time-series curve. Instantaneous pulsating frequency is the instantaneous heart rate calculated based on the time interval of a single pulsating cycle.

[0052] Specifically, the controller reads continuously acquired blood flow data from its internal buffer over a certain time period. Each blood flow data point contains a specific velocity value and a corresponding timestamp. The controller arranges these data points in chronological order according to their timestamps, forming a data sequence. By visualizing this time-series data logically or visually, a blood flow velocity time-series curve that intuitively reflects the periodic changes in blood flow velocity with the heartbeat is constructed.

[0053] Then, the controller applies a peak detection algorithm to the constructed blood flow velocity time-series curve, such as a method based on the change of the first derivative from positive to negative, to identify the peak blood flow velocity points representing the peak of each systolic heartbeat. The controller collects the values ​​of all identified peak blood flow velocity points within a preset time window, such as a sliding time period of 5 seconds. Subsequently, the controller calculates the arithmetic mean of these peak value points and uses this average as the blood flow velocity feature value at the current moment, which smoothly reflects the recent average blood perfusion level.

[0054] Next, the controller captures a segment of blood flow velocity time-series data and performs an autocorrelation function operation on it. The result generates a new function curve. The time delay corresponding to the first significant peak point on this curve, excluding the zero-delay point, is identified as the main period of the signal segment, which is the time interval of the pulsation cycle. The controller calculates the reciprocal of this time interval and converts it into a value in terms of the number of beats per minute, thus obtaining an instantaneous pulsation frequency.

[0055] The controller continuously executes the step of calculating instantaneous pulsation frequency, obtaining a series of instantaneous pulsation frequency values ​​that vary over time. Since individual instantaneous pulsation frequencies may exhibit slight fluctuations, the controller stores these values ​​in a first-in, first-out (FIFO) queue. The controller then calculates an average value by performing an arithmetic mean on all data in the queue. As new instantaneous pulsation frequency values ​​enter the queue, the oldest value is removed, and the controller recalculates the average. This continuously updated average value is the smoothed vascular pulsation frequency characteristic value.

[0056] Step S1022: Input the baseline compression pressure data into the proportional loop of the preset PID control algorithm to calculate the proportional adjustment amount that is proportional to the current compression pressure, and input the blood flow deviation signal into the integral loop of the preset PID control algorithm to perform time integration on the blood flow deviation signal to generate an integral adjustment amount;

[0057] In step S1022, the proportional element refers to the part of the PID control algorithm that proportionally amplifies the current deviation signal. The proportional adjustment is the output quantity generated by the proportional element, which is proportional to the current compression pressure. The integral element refers to the part of the PID control algorithm that calculates the cumulative effect of the deviation signal over time. The integral adjustment is the output quantity generated by the integral element, used to eliminate the steady-state error of the system.

[0058] Specifically, the controller multiplies the real-time baseline compression pressure data by a preset proportional coefficient to obtain a proportional adjustment amount, which directly reflects the current applied pressure level. Simultaneously, the controller inputs the blood flow deviation signal generated in step S1021 to the integrator, which continuously accumulates the blood flow deviation signal over time and multiplies the accumulated result by an integral coefficient to generate an integral adjustment amount. If the blood flow velocity remains below a threshold, the integral adjustment amount will continue to increase, thereby generating a continuous decompression driving force.

[0059] Step S1023: Based on the rate of change of the characteristic value of vascular pulsation frequency, the differential adjustment amount is calculated through the differential element of the preset PID control algorithm.

[0060] In step S1023, the derivative element refers to the part of the PID control algorithm that responds to the rate of change of the deviation signal. The derivative adjustment is the output quantity generated by the derivative element, used to predict the system's changing trend and suppress it in advance to prevent overshoot.

[0061] Specifically, the controller monitors the changes in the vascular pulsation frequency characteristic value obtained in step S1021 in real time. The controller calculates the rate of change of this characteristic value per unit time, i.e., the derivative. When the vascular pulsation frequency fluctuates drastically due to rapid pressure changes, its rate of change will increase significantly. The controller multiplies this rate of change by a preset differential coefficient to obtain a differential adjustment amount. The function of this adjustment amount is to produce a reverse adjustment effect when pressure changes cause heart rate instability, making the adjustment process more stable.

[0062] Step S1024: Weight and fuse the proportional control, integral control, and derivative control to obtain the PID integrated control output value, and determine the initial pressure based on the PID integrated control output value.

[0063] In step S1024, weighted fusion refers to linearly combining the proportional, integral, and derivative control variables according to their respective weighting coefficients. The PID integrated control output value refers to the final control signal obtained after weighted fusion.

[0064] Specifically, the controller algebraically sums the proportional and integral control values ​​calculated in step S1022, and the derivative control value calculated in step S1023. This summation process may involve multiplying each control value by different weighting coefficients. The final value obtained is the PID integrated control output value. Based on the sign and magnitude of this output value, the controller converts it into specific control commands for the compression hemostat actuator, such as an air pump or motor, for example, increasing or decreasing the air pressure. When the PID integrated control output value drives the system to a stable equilibrium point where blood flow and pressure are both stable, the controller determines this pressure value as the initial compression pressure.

[0065] Step S103: Monitor whether a remote intervention request signal sent by the remote monitoring terminal has been received;

[0066] In step S103, the remote monitoring terminal refers to an external device operated by medical personnel that has wireless or wired communication capabilities, such as a smartphone, tablet, or central monitoring workstation. The remote intervention request signal refers to a specific data signaling issued by the remote monitoring terminal to notify the controller to prepare to receive subsequent manual instructions.

[0067] Specifically, during operation, the controller continuously monitors its communication interface, such as Bluetooth or Wi-Fi. Internally, a background service process runs that periodically checks the communication buffer for remote intervention request signals conforming to a predefined protocol format. This signal might be a specific data packet header or a data frame containing specific authentication information and a request code. Once this signal is detected, the controller confirms that a remote intervention request has been received.

[0068] Step S104: When a remote intervention request signal is received, switch the automatic adjustment mode to the remote intervention mode.

[0069] In step S104, the remote intervention mode refers to the controller suspending autonomous adjustment and switching to a working state of receiving and executing instructions from the remote monitoring terminal.

[0070] Specifically, after the controller confirms receipt of the remote intervention request signal in step S103, it immediately changes its internal operating status flag, switching from automatic adjustment mode to remote intervention mode. This switching process first suspends or terminates the currently running preset PID control algorithm process to ensure that the output of automatic adjustment does not conflict with subsequent remote commands. Simultaneously, the controller sends an acknowledgment signal back to the remote monitoring terminal, indicating that the controller has successfully switched modes and is ready to receive further commands.

[0071] Step S105: In remote intervention mode, receive remote adjustment instructions sent by the remote monitoring terminal. The remote adjustment instructions include the target compression pressure value or pressure adjustment amount.

[0072] In step S105, the remote adjustment command refers to the specific operation command generated by the remote monitoring terminal based on the professional judgment of medical personnel and sent to the controller. The target compression pressure value refers to an absolute pressure value, requiring the controller to directly adjust the compression pressure to this value. The pressure adjustment amount refers to a relative pressure change value, requiring the controller to increase or decrease the pressure based on the current pressure.

[0073] Specifically, in remote intervention mode, the controller's communication interface remains active, waiting to receive data. When the remote monitoring terminal sends a remote adjustment command, the controller receives a data packet containing the command content. The controller parses the data packet, first verifying its integrity and the legitimacy of its source, and then reading the command type field to distinguish whether the command is to set a target compression pressure value or to increase or decrease the pressure adjustment amount. Subsequently, the controller extracts the specific value carried in the command, i.e., the target compression pressure value or pressure adjustment amount, and stores this value for use in step S106.

[0074] Step S106: Calculate the target pressure based on the remote adjustment command and the initial pressure.

[0075] In step S106, the target compression pressure refers to the precise pressure value that needs to be applied to the patient's radial artery, which is determined by combining remote manual instructions and the current status of the equipment.

[0076] Specifically, the controller first retrieves the initial compression pressure determined in step S102, or the current compression pressure continuously updated during remote intervention, as the calculation benchmark. Then, the controller performs calculations based on the type of remote adjustment command parsed in step S105. If the command is a target compression pressure value type, the target compression pressure is directly equal to the value carried in the command. If the command is a pressure adjustment amount type, the controller algebraically sums the pressure adjustment amount with the current compression pressure, and the result is the target compression pressure. After the calculation is completed, the controller also performs a safety check on the obtained target compression pressure to ensure that the value does not exceed the system's preset safe pressure upper and lower limits, preventing the risk of overpressure or pressure loss. Finally, the target compression pressure that has been confirmed to be correct will be used to control the actuator of the compression device for precise adjustment.

[0077] In one possible implementation, the target compression pressure is calculated based on the remote adjustment command and the initial compression pressure, specifically including steps S1061-S1065, as follows:

[0078] Step S1061: Parse the remote adjustment command and determine whether the type of the remote adjustment command is the target pressure value type or the pressure adjustment amount type.

[0079] In step S1061, the target pressure value type refers to one format of the remote adjustment command, which directly specifies a specific pressure value that needs to be achieved. The pressure adjustment amount type refers to another format of the remote adjustment command, which specifies the amount of pressure change that needs to be increased or decreased based on the current pressure.

[0080] Specifically, after receiving a data packet containing a remote adjustment command, the controller first accesses the protocol header or specific command field of the data packet. This field contains a built-in type identifier; for example, "0x01" indicates the target pressure value type, and "0x02" indicates the pressure adjustment amount type. The controller reads this identifier and compares it with the internally preset type definition to determine the type of the remote adjustment command, and then passes the determination result to subsequent processing steps.

[0081] Step S1062: When the type of remote adjustment command is target pressure value type, extract the target pressure value carried in the remote adjustment command, calculate the difference between the target pressure value and the initial pressure to obtain the pressure difference, and convert the pressure difference into force adjustment increment according to the preset pressure conversion coefficient.

[0082] In step S1062, the pressure difference represents the numerical difference between the target pressure value specified in the remote adjustment command and the current initial pressure of the equipment. The preset pressure conversion coefficient represents a fixed proportional constant pre-stored inside the controller, used to convert changes in pressure units into changes in control units required to drive the actuator. The force adjustment increment represents the actual adjustment step or adjustment amount that the actuator needs to perform after unit conversion.

[0083] Specifically, when the controller determines in step S1061 that the type of the remote adjustment command is a target pressure value type, the controller continues to parse the load portion of the data packet to extract the specific target pressure value contained therein, such as 160 mmHg. The controller then retrieves the current initial pressure from memory, such as 145 mmHg. The controller performs a subtraction operation, that is, 160 mmHg minus 145 mmHg, to obtain a pressure difference of +15 mmHg. Subsequently, the controller calls a preset pressure conversion coefficient to convert the 15 mmHg pressure difference into a force adjustment increment that the actuator can recognize, such as converting it into a pulse signal width that drives the air pump for a specific duration.

[0084] Step S1063: When the type of remote adjustment command is pressure adjustment amount, extract the pressure adjustment amount carried in the remote adjustment command, and determine the force adjustment direction according to the positive or negative sign of the pressure adjustment amount, where a positive value indicates the pressure increase direction and a negative value indicates the pressure decrease direction.

[0085] In step S1063, the force adjustment direction indicates whether the pressure device needs to perform a pressurization operation or a depressurization operation.

[0086] Specifically, when the controller determines in step S1061 that the type of the remote adjustment command is a pressure adjustment amount, the controller parses and extracts the pressure adjustment amount value carried in the command, such as +10mmHg or -5mmHg. The controller checks the mathematical sign of this value. If the value is positive, the controller sets the force adjustment direction to the pressure increase direction; if the value is negative, the controller sets the force adjustment direction to the pressure decrease direction. This direction information will be used to guide subsequent pressure regulation calculations.

[0087] Step S1064: Based on the force adjustment increment or pressure adjustment amount, combined with the initial compression pressure and the force adjustment direction, the target compression pressure is calculated through linear superposition calculation;

[0088] In step S1064, linear superposition operation refers to the calculation process of algebraically summing the base value with one or more incremental values.

[0089] Specifically, the controller selects different calculation paths based on the type of remote adjustment command. If the type is a target compression pressure value, the controller directly sums the pressure difference corresponding to the force adjustment increment calculated in step S1062 with the initial compression pressure, for example, 145mmHg + 15mmHg, resulting in 160mmHg as the target compression pressure. If the type is a pressure adjustment amount, the controller directly sums the pressure adjustment amount extracted in step S1063, for example, +10mmHg, with the initial compression pressure, i.e., 145mmHg + 10mmHg, resulting in 155mmHg as the target compression pressure. The entire process is a direct addition operation.

[0090] Step S1065: Perform a safety threshold check on the target compression pressure. When the target compression pressure exceeds the preset safety threshold range, correct the target compression pressure to the upper limit of the preset safety threshold range.

[0091] In step S1065, the safety threshold verification refers to comparing the calculated target compression pressure with the upper and lower limits of the system's set safety pressure to prevent unsafe operations from being performed. The preset safety threshold range refers to a pre-set range of allowable maximum and minimum compression pressure to protect patient safety.

[0092] Specifically, after calculating the target pressure in step S1064, the controller reads a preset upper limit (e.g., 200 mmHg) and a lower limit (e.g., 80 mmHg) from its safety configuration parameters. The controller compares the calculated target pressure with this range. If the target pressure is between 80 mmHg and 200 mmHg, the verification passes. If the calculated target pressure, for example, 210 mmHg, exceeds the upper limit of 200 mmHg, the controller automatically corrects the target pressure to the upper limit of 200 mmHg. The corrected value is the final command pressure issued to the actuator.

[0093] Please refer to Figure 2 , Figure 2 This is another flowchart illustrating a method for determining radial artery compression pressure disclosed in an embodiment of this application. In one possible implementation, after calculating the target compression pressure based on a remote adjustment command and the initial compression pressure, the method further includes steps S201-S209, as follows:

[0094] Step S201: Based on blood flow data, construct a vascular compliance model of the patient's radial artery. The vascular compliance model is used to characterize the nonlinear mapping relationship between the deformation characteristics of the radial artery under different compression pressures and the degree of blood flow obstruction.

[0095] In step S201, the vascular compliance model refers to a mathematical model describing the relationship between the changes in the lumen geometry, elastic deformation of the vessel wall, and internal blood flow state of the radial artery in a specific patient when subjected to external pressure. The nonlinear mapping relationship is used to indicate that the relationship between the compressive pressure and the vascular deformation and degree of blood flow obstruction is not a simple direct proportionality. For example, a small pressure increment may cause a large change in blood flow in a low-pressure area, while it may cause a small change in blood flow in a high-pressure area.

[0096] Specifically, the controller enters a model building program. In this program, the controller applies a series of precisely controlled, stepped pressures to the radial artery via a compression component. At each pressure step, the controller simultaneously acquires a segment of blood flow data. By analyzing the changes in blood flow velocity, pulsatility index, and other data corresponding to different compression pressures, the controller uses a pre-set algorithm, such as multinomial fitting or a neural network model, to build a vascular compliance model that characterizes the patient's radial artery properties. This model is parameterized and stored in the controller's memory for subsequent simulation calculations.

[0097] Step S202: Based on the vascular compliance model, calculate the stress distribution characteristics of the vascular wall under the target compression pressure, and identify the stress concentration areas in the stress distribution characteristics of the vascular wall. The stress concentration areas are potential tissue damage risk areas.

[0098] In step S202, the stress distribution characteristics of the blood vessel wall refer to the spatial distribution pattern of the combined internal and external pressures exerted on various locations of the blood vessel wall under specific compressive pressure. A stress concentration area refers to a local location in the blood vessel wall stress distribution where the stress value is significantly higher than the surrounding area. A potential tissue damage risk area refers to a stress concentration area, because excessive mechanical stress may lead to endothelial damage or pressure injury to surrounding tissues.

[0099] Specifically, the controller takes the previously calculated target compression pressure as input and substitutes it into the vascular compliance model constructed in step S201. The model uses finite element analysis or similar simulation methods to calculate a two-dimensional or three-dimensional image of the vessel wall stress distribution throughout the compressed segment of the radial artery under this target compression pressure. The controller then performs a peak search algorithm on this stress distribution data to find the point or small area with the highest stress value, and records the coordinates and peak stress magnitude of this area; this area is then identified as a stress concentration region.

[0100] Step S203: Based on the preset structural parameters of the compression component, the operating area of ​​the compression component is mapped into a two-dimensional compression matrix composed of multiple compression units.

[0101] In step S203, the preset structural parameters of the compression component refer to the inherent properties of the physical design of the compression device, including the overall size and shape of the compression component, as well as the number and arrangement of the smallest independently controllable execution units within it. A compression unit refers to the smallest physical unit in the compression component capable of independently adjusting pressure. The two-dimensional compression matrix refers to a logical data structure established at the software level by the controller for ease of management and control, corresponding one-to-one with the array of physical compression units.

[0102] Specifically, the controller reads the preset structural parameters of the compression component from its firmware configuration. For example, it learns that the compression component consists of a 5x5 square array containing 25 independently controllable compression units. Based on these parameters, the controller creates a 5x5 two-dimensional array in memory, where each element of the array uniquely corresponds to a physical compression unit. This two-dimensional array is the two-dimensional compression matrix.

[0103] Step S204: Project the location information of the stress concentration area onto the two-dimensional compression matrix to obtain the central compression element group.

[0104] In step S204, the central compression element group refers to the set of compression elements in the two-dimensional compression matrix that correspond to the geographical location and stress concentration area.

[0105] Specifically, the controller acquires the physical coordinate information of the stress concentration region identified in step S202. The controller then uses a coordinate transformation algorithm to map these physical coordinates onto the logical coordinate system of the two-dimensional compression matrix created in step S203. After mapping, the compression elements corresponding to the matrix elements covering the stress concentration region are identified by the controller and marked as the central compression element group.

[0106] Step S205: Calculate the pressure reduction for the central compression unit group based on the difference between the peak stress and the preset safe stress threshold.

[0107] In step S205, the peak stress refers to the maximum stress value within the stress concentration area. The preset safe stress threshold refers to the maximum safe stress limit that the blood vessel wall can withstand, pre-set to avoid tissue damage. The pressure reduction amount refers to the total pressure reduction required on the central compression unit group to lower the peak stress to a safe level.

[0108] Specifically, the controller compares the stress peak obtained in step S202 with a preset safe stress threshold stored in the configuration. If the stress peak exceeds the threshold, the controller calculates the difference between the two. The controller then performs inverse calculations using a vascular compliance model to determine how much pressure needs to be reduced to bring the stress peak down to the preset safe stress threshold. This calculated pressure value is the pressure reduction amount.

[0109] Step S206: Based on the pressure reduction amount, apply a preset pressure distribution function to generate a pressure attenuation value for each compression unit in the central compression unit group.

[0110] In step S206, the pressure distribution function refers to a mathematical function, such as a Gaussian distribution function, used to determine how the total pressure reduction is smoothly distributed to the individual compression units within the central compression unit group. The pressure attenuation value refers to the specific pressure reduction required for each individual compression unit within the central compression unit group.

[0111] Specifically, the controller uses the center point of the stress concentration region as the peak point and applies a preset pressure distribution function, such as a two-dimensional Gaussian function. The controller calculates the weighting coefficient for each compression unit within the central compression unit group based on its distance from the peak point. Subsequently, the controller distributes the total pressure reduction obtained in step S205 according to these weighting coefficients, calculating a specific pressure attenuation value for each central compression unit. Compression units closer to the peak point receive a larger pressure attenuation value.

[0112] Step S207: The pressure reduction amount is allocated to the peripheral compression units in the two-dimensional compression matrix, excluding the central compression unit group, with a weight inversely proportional to the distance from the central compression unit group, and the pressure compensation value is calculated for each peripheral compression unit.

[0113] In step S207, peripheral compression units refer to all compression units in the two-dimensional compression matrix except for the central compression unit group. The pressure compensation value refers to the pressure value that needs to be added to the peripheral compression units in order to maintain the overall hemostatic effect while reducing the pressure in the central region.

[0114] Specifically, the controller iterates through all elements marked as peripheral compression units in the two-dimensional compression matrix. For each peripheral compression unit, the controller calculates its distance from the geometric center of the central compression unit group. The controller uses the total pressure reduction calculated in step S205 as the total pressure to be compensated, and distributes this total pressure compensation amount to all peripheral compression units based on the reciprocal of the distance as a weight. The closer the peripheral compression unit is to the center, the higher the pressure compensation value it receives.

[0115] Step S208: Algebraically superimpose the target pressure of each compression unit in the two-dimensional compression matrix with the corresponding pressure attenuation value or pressure compensation value to generate a target pressure distribution matrix, and send the target pressure distribution matrix to the compression component.

[0116] In step S208, the target pressure distribution matrix refers to a two-dimensional array containing the final target pressure values ​​of all compression units in the two-dimensional compression matrix, and is the final execution instruction sent to the compression component.

[0117] Specifically, the controller first fills the entire two-dimensional pressure matrix with the target pressure value. Then, the controller iterates through the matrix. For each pressure unit belonging to the central pressure unit group, the controller subtracts the pressure attenuation value calculated in step S206 from its current target pressure value; for each pressure unit belonging to the peripheral pressure units, the controller adds the pressure compensation value calculated in step S207 to its current target pressure value. After completing the calculation for all units, the resulting two-dimensional matrix is ​​the target pressure distribution matrix.

[0118] Step S209: Send the target pressure distribution matrix to the compression component.

[0119] In step S209, sending the target pressure distribution matrix to the compression component means that the controller transmits a complete set of instructions containing the target pressure value of each compression unit to the drive circuit of the compression component through the internal data bus or communication interface.

[0120] Specifically, the controller formats and packages the target pressure distribution matrix generated in step S208 according to the communication protocol agreed upon with the compression component hardware. Then, the controller sends this data packet to the microcontroller or driver chip of the compression component through its output port. After receiving the data, the compression component parses the pressure value corresponding to each compression unit and drives its respective actuator, such as a miniature valve or motor, to precisely adjust the pressure of each unit, thereby achieving a non-uniform, optimized pressure distribution.

[0121] Reference Figure 3 This application also provides a radial artery compression pressure determination device, which includes a data acquisition module 301, an automatic adjustment module 302, a monitoring module 303, a mode adjustment module 304, a remote intervention module 305, and a pressure determination module 306. Specifically: the data acquisition module 301 acquires baseline compression pressure data and blood flow data measured by sensors; the automatic adjustment module 302 determines the initial compression pressure based on a preset PID control algorithm and the baseline compression pressure data and blood flow data in automatic adjustment mode; the monitoring module 303 monitors whether a remote intervention request signal sent by a remote monitoring terminal is received; the mode adjustment module 304 switches the automatic adjustment mode to remote intervention mode when a remote intervention request signal is received; the remote intervention module 305 receives a remote adjustment command sent by the remote monitoring terminal in remote intervention mode, the remote adjustment command including a target compression pressure value or a pressure adjustment amount; and the pressure determination module 306 calculates the target compression pressure based on the remote adjustment command and the initial compression pressure.

[0122] In one possible implementation, the automatic adjustment module 302 determines the initial compression pressure based on a preset PID control algorithm, according to baseline compression pressure data and blood flow data. Specifically, the automatic adjustment module 302 extracts blood flow velocity feature values ​​and vascular pulsation frequency feature values ​​from the blood flow data, compares the blood flow velocity feature values ​​with a preset blood flow threshold, and generates a blood flow deviation signal. The automatic adjustment module 302 inputs the baseline compression pressure data into the proportional loop of the preset PID control algorithm to calculate a proportional adjustment amount proportional to the current compression pressure, and inputs the blood flow deviation signal into the integral loop of the preset PID control algorithm to perform time integration on the blood flow deviation signal and generate an integral adjustment amount. The automatic adjustment module 302 calculates the differential adjustment amount based on the rate of change of the vascular pulsation frequency feature value through the derivative loop of the preset PID control algorithm. The automatic adjustment module 302 weights and fuses the proportional adjustment amount, integral adjustment amount, and differential adjustment amount to obtain a PID comprehensive adjustment output value, and determines the initial compression pressure based on the PID comprehensive adjustment output value.

[0123] In one possible implementation, the automatic adjustment module 302 extracts blood flow velocity feature values ​​and vascular pulsation frequency feature values ​​based on blood flow data. Specifically, the automatic adjustment module 302 constructs a blood flow velocity time-series curve based on the blood flow data; the automatic adjustment module 302 performs peak detection on the blood flow velocity time-series curve, identifies the peak points of blood flow velocity within each cardiac cycle, and calculates the average value of all blood flow velocity peak points within a preset time window as the blood flow velocity feature value; the automatic adjustment module 302 performs periodic analysis on the blood flow velocity time-series curve, uses the autocorrelation function method to identify the time interval between adjacent pulsation cycles, and calculates the reciprocal of the time interval as the instantaneous pulsation frequency; the automatic adjustment module 302 performs moving average filtering on multiple instantaneous pulsation frequencies within the preset time window to obtain the vascular pulsation frequency feature value.

[0124] In one possible implementation, before the automatic adjustment module 302 determines the initial compression pressure based on the baseline compression pressure data and blood flow data using a preset PID control algorithm, the method further includes: the automatic adjustment module 302 acquiring the patient's baseline physiological parameter information, including the patient's age, weight, baseline blood pressure, and coagulation function indicators; the automatic adjustment module 302 matching the corresponding PID control parameter group from a preset parameter configuration library based on the baseline physiological parameter information, the PID control parameter group including the proportional coefficient, integral time constant, and derivative time constant; and the automatic adjustment module 302 loading the PID control parameter group into the preset PID control algorithm to complete the personalized parameter initialization of the preset PID control algorithm.

[0125] In one possible implementation, the pressure determination module 306 calculates the target pressure based on the remote adjustment command and the initial pressure. Specifically, this includes: the pressure determination module 306 parses the remote adjustment command and determines whether the command type is a target pressure value type or a pressure adjustment amount type; when the remote adjustment command type is a target pressure value type, the pressure determination module 306 extracts the target pressure value carried in the remote adjustment command, calculates the difference between the target pressure value and the initial pressure to obtain a pressure difference, and converts the pressure difference into a force adjustment increment according to a preset pressure conversion coefficient; when the remote adjustment command... When the type is pressure adjustment amount, the pressure determination module 306 extracts the pressure adjustment amount carried in the remote adjustment command, and determines the force adjustment direction according to the positive or negative sign of the pressure adjustment amount, where a positive value indicates the pressure increase direction and a negative value indicates the pressure decrease direction; the pressure determination module 306 calculates the target pressure through linear superposition operation based on the force adjustment increment or pressure adjustment amount, combined with the initial compression pressure and the force adjustment direction; the pressure determination module 306 performs a safety threshold verification on the target pressure, and when the target pressure exceeds the preset safety threshold range, the pressure determination module 306 corrects the target pressure to the upper limit of the preset safety threshold range.

[0126] In one possible implementation, after the pressure determination module 306 calculates the target compression pressure based on the remote adjustment command and the initial compression pressure, the method further includes: the pressure determination module 306 constructing a vascular compliance model of the patient's radial artery based on blood flow data; the vascular compliance model characterizes the nonlinear mapping relationship between the deformation characteristics of the radial artery under different compression pressures and the degree of blood flow obstruction; the pressure determination module 306 calculating the vascular wall stress distribution characteristics under the target compression pressure based on the vascular compliance model, and identifying stress concentration areas in the vascular wall stress distribution characteristics, where stress concentration areas are potential tissue damage risk areas; and the pressure determination module 306 performing pressure compensation or pressure reduction based on the location information and stress peak value of the stress concentration areas, generating a target pressure distribution matrix, and sending the target pressure distribution matrix to the compression component.

[0127] In one possible implementation, the pressure determination module 306 performs pressure compensation or pressure reduction based on the location information of the stress concentration area and the stress peak value, generating a target pressure distribution matrix. Specifically, the pressure determination module 306 maps the operating area of ​​the compression component into a two-dimensional compression matrix composed of multiple compression units based on preset structural parameters of the compression component; the pressure determination module 306 projects the location information of the stress concentration area onto the two-dimensional compression matrix to obtain a central compression unit group; the pressure determination module 306 calculates the pressure reduction amount for the central compression unit group based on the difference between the stress peak value and a preset safe stress threshold. The pressure determination module 306 generates a pressure attenuation value for each compression unit in the central compression unit group based on the pressure reduction amount and a preset pressure distribution function. The pressure determination module 306 then distributes the pressure reduction amount, with a weight inversely proportional to the distance from the central compression unit group, to the peripheral compression units in the two-dimensional compression matrix, and calculates a pressure compensation value for each peripheral compression unit. The pressure determination module 306 algebraically superimposes the target compression pressure of each compression unit in the two-dimensional compression matrix with the corresponding pressure attenuation value or pressure compensation value to generate a target pressure distribution matrix, and sends the target pressure distribution matrix to the compression component.

[0128] It should be noted that the apparatus provided in the above embodiments is only illustrated by the division of the above functional modules. 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.

[0129] This application also provides an electronic device. (See reference...) Figure 4 , Figure 4 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. The electronic device 400 may include: at least one processor 401, at least one network interface 404, a user interface 403, a memory 405, and at least one communication bus 402.

[0130] The communication bus 402 is used to enable communication between these components.

[0131] The user interface 403 may include a display screen and a camera. Optionally, the user interface 403 may also include a standard wired interface and a wireless interface.

[0132] The network interface 404 may optionally include a standard wired interface or a wireless interface (such as a Wi-Fi interface).

[0133] The processor 401 may include one or more processing cores. The processor 401 connects to various parts of the server using various interfaces and lines, and performs various server functions and processes data by running or executing instructions, programs, code sets, or instruction sets stored in memory 405, and by calling data stored in memory 405. Optionally, the processor 401 may be implemented using at least one hardware form of Digital Signal Processing (DSP), Field-Programmable Gate Array (FPGA), or Programmable Logic Array (PLA). The processor 401 may integrate one or a combination of several of the following: Central Processing Unit (CPU), Graphics Processing Unit (GPU), and modem. The CPU primarily handles the operating system, user interface, and applications; the GPU is responsible for rendering and drawing the content required for display; and the modem handles wireless communication. It is understood that the modem may also be implemented as a separate chip without being integrated into the processor 401.

[0134] The memory 405 may include random access memory (RAM) or read-only memory. Optionally, the memory 405 may include a non-transitory computer-readable storage medium. The memory 405 may be used to store instructions, programs, code, code sets, or instruction sets. The memory 405 may include a program storage area and a data storage area, wherein the program storage area may store instructions for implementing an operating system, instructions for at least one function (such as touch function, sound playback function, image playback function, etc.), instructions for implementing the above-described method embodiments, etc.; the data storage area may store data involved in the above-described method embodiments, etc. Optionally, the memory 405 may also be at least one storage device located remotely from the aforementioned processor 401. (Refer to...) Figure 4 The memory 405, which serves as a computer storage medium, may include an operating system, a network communication module, a user interface module, and an application program for determining radial artery compression pressure.

[0135] exist Figure 4 In the illustrated electronic device 400, the user interface 403 is mainly used to provide an input interface for the user and acquire user input data; while the processor 401 can be used to call an application program stored in the memory 405 for determining radial artery compression pressure. When executed by one or more processors 401, the electronic device 400 performs one or more of the methods described in the above embodiments. It should be noted that, for the foregoing method embodiments, for the sake of simplicity, they are all described as a series of actions. However, those skilled in the art should understand that this application is not limited to the described order of actions, because according to this application, some steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also understand that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily essential to this application.

[0136] This application also provides a computer-readable storage medium storing instructions. When executed by one or more processors 401, these instructions cause the electronic device 400 to perform one or more of the methods described in the above embodiments.

[0137] In the above embodiments, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions in other embodiments.

[0138] In the various embodiments provided in this application, it should be understood that the disclosed apparatus can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some service interface; the indirect coupling or communication connection between apparatuses or units may be electrical or other forms.

[0139] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0140] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0141] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage device (CMD). Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a memory and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this application. The aforementioned memory includes various media capable of storing program code, such as USB flash drives, portable hard drives, magnetic disks, or optical disks.

[0142] The above description is merely an exemplary embodiment of this disclosure and should not be construed as limiting the scope of this disclosure. Any equivalent changes and modifications made in accordance with the teachings of this disclosure shall still fall within the scope of this disclosure. Other embodiments of this disclosure will be readily apparent to those skilled in the art upon consideration of the specification and the disclosure of practical truths.

[0143] This application is intended to cover any variations, uses, or adaptations of this disclosure that follow the general principles of this disclosure and include common knowledge or customary techniques in the art not described in this disclosure. The specification and embodiments are to be considered exemplary only, and the scope and spirit of this disclosure are defined by the claims.

Claims

1. A device for determining radial artery compression pressure, characterized in that, The device includes a data acquisition module (301), an automatic adjustment module (302), a monitoring module (303), a mode adjustment module (304), a remote intervention module (305), and a pressure determination module (306), wherein: The data acquisition module (301) is used to acquire the basic compression pressure data and blood flow data measured by the sensor; The automatic adjustment module (302) is used to determine the initial compression pressure based on the basic compression pressure data and the blood flow data in the automatic adjustment mode, according to a preset PID control algorithm. The monitoring module (303) is used to monitor whether a remote intervention request signal sent by the remote monitoring terminal is received; The mode adjustment module (304) is used to switch the automatic adjustment mode to the remote intervention mode when the remote intervention request signal is received; The remote intervention module (305) is used to receive a remote adjustment command sent by the remote monitoring terminal in the remote intervention mode. The remote adjustment command includes a target compression pressure value or a pressure adjustment amount. The pressure determination module (306) is used to calculate the target pressure based on the remote adjustment command and the initial pressure. After the pressure determination module (306) calculates the target pressure based on the remote adjustment command and the initial pressure, it also includes: The pressure determination module (306) constructs a vascular compliance model of the patient's radial artery based on blood flow data. The vascular compliance model is used to characterize the nonlinear mapping relationship between the deformation characteristics of the radial artery under different compression pressures and the degree of blood flow obstruction. The pressure determination module (306) calculates the stress distribution characteristics of the blood vessel wall under the target compression pressure based on the blood vessel compliance model, and identifies the stress concentration area in the stress distribution characteristics of the blood vessel wall. The stress concentration area is the area with potential tissue damage risk. The pressure determination module (306) performs pressure compensation or pressure reduction based on the location information of the stress concentration area and the stress peak, generates a target pressure distribution matrix, and sends the target pressure distribution matrix to the compression component; The pressure determination module (306) performs pressure compensation or pressure reduction based on the location information and peak stress of the stress concentration area, generating a target pressure distribution matrix, specifically including: The pressure determination module (306) maps the operating area of ​​the pressure component into a two-dimensional pressure matrix composed of multiple pressure units based on the preset structural parameters of the pressure component. The pressure determination module (306) projects the location information of the stress concentration area onto the two-dimensional compression matrix to obtain the central compression unit group; The pressure determination module (306) calculates the pressure reduction for the central compression unit group based on the difference between the peak stress and the preset safe stress threshold. The pressure determination module (306) generates a pressure attenuation value for each compression unit in the central compression unit group based on the pressure reduction amount and a preset pressure distribution function. The pressure determination module (306) assigns the pressure reduction amount, with a weight inversely proportional to the distance from the central pressure unit group, to the peripheral pressure units in the two-dimensional pressure matrix other than the central pressure unit group, and calculates the pressure compensation value for each peripheral pressure unit. The pressure determination module (306) algebraically superimposes the target pressure of each pressure unit in the two-dimensional pressure matrix with the corresponding pressure attenuation value or pressure compensation value to generate a target pressure distribution matrix, and sends the target pressure distribution matrix to the pressure component.

2. The apparatus according to claim 1, characterized in that, The automatic adjustment module (302) determines the initial compression pressure based on a preset PID control algorithm, according to the baseline compression pressure data and blood flow data, specifically including: The automatic adjustment module (302) extracts blood flow velocity feature values ​​and vascular pulsation frequency feature values ​​based on blood flow data, and compares the blood flow velocity feature values ​​with a preset blood flow threshold to generate a blood flow deviation signal; The automatic adjustment module (302) inputs the basic compression pressure data into the proportional link of the preset PID control algorithm to calculate the proportional adjustment amount that is proportional to the current compression pressure, and inputs the blood flow deviation signal into the integral link of the preset PID control algorithm to perform time integration calculation on the blood flow deviation signal to generate an integral adjustment amount. The automatic adjustment module (302) calculates the differential adjustment amount based on the rate of change of the characteristic value of vascular pulsation frequency through the differential element of the preset PID control algorithm; The automatic adjustment module (302) weights and fuses the proportional adjustment, integral adjustment and derivative adjustment to obtain the PID comprehensive adjustment output value, and determines the initial pressure based on the PID comprehensive adjustment output value.

3. The apparatus according to claim 2, characterized in that, The automatic adjustment module (302) extracts blood flow velocity feature values ​​and vascular pulsation frequency feature values ​​based on blood flow data, specifically including: The automatic adjustment module (302) constructs a blood flow velocity time-series curve based on blood flow data; the automatic adjustment module (302) performs peak detection on the blood flow velocity time-series curve, identifies the peak point of blood flow velocity in each cardiac cycle, and calculates the average value of all blood flow velocity peak points in a preset time window as the blood flow velocity feature value; The automatic adjustment module (302) performs periodic analysis on the blood flow velocity time-series curve, uses the autocorrelation function method to identify the time interval between adjacent pulsation cycles, and calculates the reciprocal of the time interval as the instantaneous pulsation frequency; The automatic adjustment module (302) performs a moving average filter on multiple instantaneous pulsation frequencies within a preset time window to obtain the vascular pulsation frequency characteristic value.

4. The apparatus according to claim 1, characterized in that, Before the automatic adjustment module (302) determines the initial compression pressure based on the baseline compression pressure data and blood flow data using a preset PID control algorithm, the following steps are also included: The automatic adjustment module (302) acquires the patient's basic physiological parameters, including the patient's age, weight, baseline blood pressure, and coagulation function indicators. The automatic adjustment module (302) matches the corresponding PID control parameter group from the preset parameter configuration library based on the basic physiological parameter information. The PID control parameter group includes the proportional coefficient, integral time constant and derivative time constant. The automatic adjustment module (302) loads the PID control parameter group into the preset PID control algorithm and completes the personalized parameter initialization of the preset PID control algorithm.

5. The apparatus according to claim 1, characterized in that, The pressure determination module (306) calculates the target pressure based on the remote adjustment command and the initial pressure, specifically including: The pressure determination module (306) parses the remote adjustment command and determines whether the type of the remote adjustment command is the target pressure value type or the pressure adjustment amount type. When the type of the remote adjustment command is the target pressure value type, the pressure determination module (306) extracts the target pressure value carried in the remote adjustment command, calculates the difference between the target pressure value and the initial pressure to obtain the pressure difference, and converts the pressure difference into the force adjustment increment according to the preset pressure conversion coefficient. When the type of the remote adjustment command is the pressure adjustment amount type, the pressure determination module (306) extracts the pressure adjustment amount carried in the remote adjustment command and determines the force adjustment direction according to the positive or negative sign of the pressure adjustment amount, where a positive value indicates the pressure increase direction and a negative value indicates the pressure decrease direction. The pressure determination module (306) calculates the target pressure based on the force adjustment increment or pressure adjustment amount, combined with the initial pressure and the force adjustment direction, through linear superposition. The pressure determination module (306) performs a safety threshold check on the target compression pressure. When the target compression pressure exceeds the preset safety threshold range, the pressure determination module (306) corrects the target compression pressure to the upper limit of the preset safety threshold range.

Images