Compression protection auxiliary control system for carotid artery puncture point

Abstract

The invention relates to the technical field of compression protection assistance, and provides a compression protection auxiliary control system for a carotid artery puncture point, which comprises a signal integration module, a compression force optimization control module, a transient response module and a real-time monitoring module. The signal integration module is responsible for collecting pressure, displacement, acceleration and electromyographic signals around a puncture point and processing data to generate an image reflecting a mechanical state; the compression force optimization control module dynamically adjusts the target compression force distribution of the positions of the sensors based on real-time monitoring data so as to adapt to the pressure requirements of the patient in different states; the transient response module is responsible for identifying non-autonomous actions of a patient, and by analyzing action types and deviation amplitudes, the compression force is adjusted in real time when the actions occur, so that the influence of transient actions on puncture points is reduced; the real-time monitoring module can upload the patient data to a cloud server, and when the pressure fluctuates or the action frequency exceeds a preset threshold value, early warning information is sent to medical staff.

Description

Technical Field

[0001] The present invention relates to the technical field of compression protection assistance, and more specifically, to a compression protection assistance control system for a carotid artery puncture point. Background Art

[0002] After carotid stenting, support and protection of the puncture site is particularly important to ensure patient safety and accelerate recovery. Patients are usually required to rest in bed after surgery to reduce unexpected stress caused by activities. However, during the recovery period, even in bed, patients will inevitably make some involuntary movements, such as coughing, sneezing, or muscle contractions. These movements are transmitted to the chest and neck muscles through nerve reflexes, causing instantaneous pressure fluctuations in the puncture site area, increasing the risk of bleeding or stent displacement. Therefore, the use of a compression protection device helps maintain the stability of the puncture site after surgery, reduce the impact of these unconscious movements on the puncture site, and ensure the smooth progress of the patient's recovery process.

[0003] Document 1 (Colapinto, RF, Harty, PW, & Cook, Inc. (1988). Femoral artery compression device for outpatient angiography. Radiology, 166 (3), 890-891.) describes a compression device after femoral artery puncture. This type of device is mainly used for vascular puncture care of patients and is intended to provide constant pressure to avoid bleeding and hematoma. The document points out that by applying continuous pressure at the femoral artery puncture site, the device can effectively prevent delayed postoperative bleeding, and the pressure can be maintained even when the patient is standing.

[0004] In order to better protect the puncture point and cope with the sudden pressure fluctuations that may occur in patients after surgery, the compression protection device should have the function of automatically adjusting the compression force so as to adjust the pressure in time according to different movements or changes in body position. This is because the unconscious movements of patients during recovery often lead to an instantaneous increase in local pressure, and traditional devices cannot respond quickly, which can easily cause additional burden on the puncture point. Automatically adjusting the compression force can respond to these physiological changes in real time, reduce the impact on the puncture point, ensure that the device always provides appropriate support, and thus improve the reliability and effectiveness of puncture point protection.

[0005] Reference 2 (Mosti, G., & Partsch, H. (2018). A wearable compression device to normalise calf muscle pump function in chronic venous insufficiency for each postural position. European Journal of Vascular and Endovascular Surgery) introduces an IntelliwPress wearable device that automatically adjusts the pressure, which is designed to help patients with chronic venous insufficiency enhance the function of the venous pump by adjusting the pressure. The IntelliwPress device is equipped with an accelerometer and a pressure sensor, which can identify changes in the patient's body position and adjust the compression force accordingly, thereby maintaining the required venous support in the supine, standing or walking positions. Studies have shown that the device is superior to traditional elastic stockings in improving venous return in the patient's lower limbs, especially during long-term standing and walking. However, IntelliwPress is mainly aimed at protecting the venous function of the lower limbs, and lacks the ability to respond quickly and finely to sudden pressure fluctuations at the carotid puncture site. In carotid stent puncture protection, pressure changes are frequent and sudden.

[0006] In order to solve the above problems, a technical solution is now provided. Summary of the invention

[0007] In order to overcome the above-mentioned defects of the prior art, the present invention provides a compression protection auxiliary control system for the carotid artery puncture point. The system combines a compression force optimization control module, an instantaneous response module and a real-time monitoring module. By real-time monitoring of the patient's electromyographic signals, displacement signals and acceleration signals, the system identifies the patient's instantaneous action type and deviation amplitude and automatically adjusts the compression force accordingly, thereby achieving dynamic adaptive adjustment of the puncture point pressure, thereby ensuring the stability of the puncture point and preventing the stent from shifting.

[0008] To achieve the above object, the present invention provides the following technical solutions:

[0009] A compression protection auxiliary control system for a carotid artery puncture point, comprising a signal integration module, a compression force optimization control module, an instantaneous response module and a real-time monitoring module, and further comprising and, wherein the signal integration module is respectively connected to the compression force optimization control module, the instantaneous response module and the real-time monitoring module, the compression force optimization control module and the instantaneous response module are bidirectionally connected, and the real-time monitoring module is respectively connected to the compression force optimization control module and the instantaneous response module;

[0010] The pressure force optimization module is used to analyze sensor data in real time, dynamically adjust the pressure force distribution during the compression protection process of the carotid stent puncture point, and generate target applied force distribution parameters for each sensor position, including a pressure force distribution optimization unit, a feedback control unit and a state analysis unit, wherein the pressure force distribution optimization unit is used to calculate the target pressure value of each sensor position based on the real-time pressure data of each sensor through the pressure force distribution calculation formula; the feedback control unit is used to adaptively adjust the actual pressure according to the signal transmitted by the state analysis unit after the pressure force distribution optimization unit completes the target pressure calculation of each sensor position, so as to meet the pressure requirements of the patient in a static state and instantaneous action; the state analysis unit is used to analyze the patient's electromyographic signal, displacement signal and acceleration signal, identify the patient's static state and instantaneous action through the state evaluation value, and send a signal to the feedback control unit when the state changes; wherein the pressure force distribution calculation formula is:

[0011]

[0012] In the formula, F i is the target pressure at the i-th sensor position, T is the total pressure setting value, C i The real-time pressure value measured by each sensor, K i A compensation parameter that changes according to the patient's real-time status;

[0013] The instantaneous response module is used to monitor and identify the patient's instantaneous movement type and deviation amplitude in real time, and dynamically adjust the pressure during the instantaneous movement according to the movement type and deviation amplitude information, and includes a movement recognition unit and a pressure adjustment unit.

[0014] As a further solution of the present invention, the compensation parameter is dynamically adjusted according to the real-time state change of the patient, and the formula is:

[0015] K i =G·(1+E i );

[0016] Where G is the mechanical response gain coefficient, E i is the normalized value of the electromyographic signal.

[0017] As a further solution of the present invention, the feedback control unit receives the target pressure setting value for each sensor position transmitted by the pressure distribution optimization unit, and maintains the pressure setting value through a proportional-integral-differential control algorithm when the patient is in a static state; when the recovery signal transmitted by the state analysis unit is received, the feedback control unit immediately adjusts the proportional, integral and differential control coefficients in real time based on the fuzzy control algorithm to perform pressure regulation operations.

[0018] As a further solution of the present invention, the feedback control unit adjusts the proportional coefficient, integral coefficient and differential coefficient in real time through a fuzzy control algorithm; wherein, when it is detected that the patient's electromyographic signal intensity exceeds the preset fluctuation threshold of the baseline electromyographic signal, the displacement signal exceeds the preset fluctuation range of the baseline displacement, or the change amplitude of the acceleration signal exceeds the preset fluctuation range of the baseline acceleration, the fuzzy control algorithm increases the proportional coefficient to the increment of the current set value, and simultaneously reduces the differential coefficient to the decrement of the current set value.

[0019] As a further solution of the present invention, the state analysis unit is used to monitor and analyze the patient's electromyographic signal, displacement signal and acceleration signal in real time, and judge the patient's physiological state by calculating the state evaluation value; wherein the calculation formula of the state evaluation value is:

[0020] R=α·|M-M0|+β·|V-V0|+γ·|A-A0|;

[0021] Where M is the real-time EMG signal, M0 is the reference EMG signal, V is the real-time displacement signal, V0 is the reference displacement signal, A is the real-time acceleration signal, A0 is the reference acceleration signal, and parameters α, β, and γ are the weight coefficients of the EMG signal, displacement signal, and acceleration signal, respectively.

[0022] As a further solution of the present invention, when the state evaluation value exceeds a preset instantaneous action threshold and the instantaneous change amplitude of the acceleration signal reaches a specific increment, the state analysis unit sends an instantaneous action trigger signal to the instantaneous response module; when the state evaluation value returns to within the resting threshold range, the state analysis unit sends a restoring signal to the feedback control unit.

[0023] As a further solution of the present invention, the action recognition unit is used to monitor the electromyographic signal, the pressure signal and the acceleration signal in real time, evaluate the deviation amplitude, and input the frequency change of the electromyographic signal, the rate of change of the pressure signal and the rate of change of the acceleration signal into the trained support vector machine model, and classify the input feature data to identify the feature patterns of different instantaneous actions; wherein, the calculation formula for evaluating the deviation amplitude is:

[0024]

[0025] Where M i is the electromyographic signal at the current moment, M0 is the reference electromyographic signal in the resting state, P i is the pressure signal at the current moment, P0 is the reference pressure signal in the resting state, D i is the deviation magnitude evaluation value.

[0026] As a further solution of the present invention, the pressure adjustment unit dynamically adjusts the pressure based on the action type and deviation amplitude information transmitted by the action recognition unit to balance the pressure impact of the instantaneous action on the puncture point and ensure that the area around the puncture point is supported during the instantaneous action. The pressure adjustment unit calculates the adjusted pressure value according to the following formula:

[0027]

[0028] In the formula, F r is the adjusted pressure, F base is the initial set pressure force, k is the adjustment coefficient related to the action type, which is set according to different action types, D i is the deviation amplitude evaluation value, and n is the adjustment index.

[0029] As a further solution of the present invention, the real-time monitoring module is used to upload the patient's sensor data through the cloud server, and send an early warning message to the mobile terminal of the medical staff when it is detected that the instantaneous action frequency or pressure fluctuation exceeds a preset threshold.

[0030] As a further solution of the present invention, the signal integration module is used to collect pressure signals, displacement signals, acceleration signals and electromyographic signals of the puncture point and its surrounding areas in real time through sensors, perform noise filtering and signal enhancement on the collected data, and fuse the processed data through multi-channel signal mapping to form a mechanical state diagram, which includes a pressure force distribution heat map, an electromyographic signal map, a displacement vector map and an acceleration time series map.

[0031] Compared with the prior art, the advantageous effects of the compression protection auxiliary control system for the carotid artery puncture point of the present invention are:

[0032] The compression protection auxiliary system of the present invention realizes real-time dynamic adjustment of the puncture point pressure through the collaborative work of multiple modules for the carotid artery puncture point. Especially when the patient has an involuntary instantaneous action, the instantaneous response module quickly identifies the action type and deviation amplitude and automatically adjusts the compression force to reduce the force impact on the puncture point. Although the IntelliwPress device in Document 2 can automatically adjust the lower limb venous pressure when the body position changes, it cannot quickly adjust the compression force for instantaneous violent actions, and lacks the ability to respond to sudden changes in local pressure at the puncture point.

[0033] The present invention collects myoelectric, displacement, acceleration and pressure signals of the puncture point through the signal integration module, analyzes the patient's physiological state in real time, and enables the pressure optimization module to accurately set the target pressure under different states, and combines the feedback control module to provide timely pressure adjustment to achieve high-precision protection of the puncture point. However, Document 2 mainly relies on the hierarchical adjustment of fixed pressure, and does not make designs for multi-signal fusion and rapid feedback optimization, which is not flexible enough in dealing with complex physiological dynamic changes. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] Figure 1 This is a diagram of the compression device in document 1.

[0035] Figure 2 Figure 2 shows the IntelliwPressure device used for the leg in the supine position (A) and the standing position (B).

[0036] Figure 3 The present invention is a flow chart of a compression protection auxiliary control system for a carotid artery puncture point.

[0037] Figure 4 The present invention is a mechanical state diagram of a compression protection auxiliary control system for a carotid artery puncture point.

[0038] In the figure, supine: supine; standing: standing; Pressure Distribution Heatmap: pressure distribution heatmap; Position X: position X axis; Position Y: position Y axis; Pressure (mmHg): pressure (mmHg); Acceleration over Time: acceleration over time; Time (s): time (seconds); Acceleration (m / s 2 ): acceleration (meters per second squared); EMG Signal Waveform: electromyographic signal waveform; EMG Signal (μV): electromyographic signal (microvolt). DETAILED DESCRIPTION

[0039] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0040] Example 1

[0041] A compression protection auxiliary control system for a carotid artery puncture point comprises a signal integration module, a compression force optimization control module, an instantaneous response module and a real-time monitoring module.

[0042] The signal integration module in the embodiment of the present invention is respectively connected to the pressure optimization control module, the transient response module and the real-time monitoring module; the pressure optimization control module and the transient response module are bidirectionally connected; and the real-time monitoring module is respectively connected to the pressure optimization control module and the transient response module.

[0043] The signal integration module is used to collect pressure signals, displacement signals, acceleration signals and electromyographic signals of the puncture point and its surrounding areas in real time through sensors, perform noise filtering and signal enhancement on the collected data, and fuse the processed data through multi-channel signal mapping to form a mechanical state diagram.

[0044] The mechanical state diagram in the embodiment of the present invention is composed of a pressure distribution heat map, an electromyographic signal map, a displacement vector map and an acceleration time series map. The pressure distribution heat map uses color gradient to represent the real-time pressure intensity of different sensor positions; the displacement vector map is based on the data of the patient's neck movement and body position changes, and displays the displacement of the puncture point relative to the baseline through vector arrows. The length and direction of the arrow reflect the relative displacement amplitude and direction of the patient during instantaneous movement; the acceleration time series map presents the change trend of the acceleration signal of the patient during the instantaneous action over time in the form of a curve; the electromyographic signal map is based on the change in muscle activity intensity, and presents the real-time collected electromyographic signal in the form of a waveform graph, and the waveform amplitude in the figure reflects the change in the intensity of the electromyographic signal.

[0045] The compression force optimization module is used to analyze sensor data in real time, dynamically adjust the compression force distribution during the compression protection process of the carotid stent puncture point, and generate target applied force distribution parameters for each sensor position, including a compression force distribution optimization unit, a feedback control unit and a state analysis unit.

[0046] The pressure distribution optimization unit in the embodiment of the present invention is used to calculate the target pressure value of each sensor position based on the real-time pressure data of each sensor through the pressure distribution calculation formula, so as to ensure that the pressure in each area is relatively balanced and reduce the risk of local pressure on the puncture point.

[0047] The calculation formula for the pressure distribution in the embodiment of the present invention is:

[0048]

[0049] In the formula, F i is the target pressure at the i-th sensor position, T is the total pressure setting value, C i The real-time pressure value measured by each sensor, Ki It is a compensation parameter that changes according to the patient's real-time status.

[0050] The compensation parameter in the embodiment of the present invention is dynamically adjusted according to the real-time state change of the patient, and its formula is:

[0051] K i =G·(1+E i )

[0052] Where G is the mechanical response gain coefficient, E i is the normalized value of the electromyographic signal.

[0053] The mechanical response gain coefficient in the embodiment of the present invention is obtained by the following steps:

[0054] Step A1, the pressure sensor and the electromyographic sensor simultaneously collect the electromyographic signal strength and the corresponding pressure feedback value of the patient in different body positions and movement states;

[0055] Step A2, applying Kalman filtering to perform noise filtering and smoothing on the electromyographic signal and pressure data;

[0056] Step A3, extracting characteristic values ​​directly related to the action and pressure from the preprocessed data, including the root mean square and frequency components of the electromyographic signal, and the average and peak values ​​of the pressure signal;

[0057] Step A4, normalizing the above feature data to adjust it to a standardized value range, so as to compare data of different dimensions in subsequent calculations;

[0058] In step A5, the corresponding pressure change is used as the dependent variable, and the functional relationship between the two is fitted by the least squares method. The regression coefficient calculated during the fitting process is the sensitivity coefficient of the system to electromyographic fluctuations and pressure changes, namely the "mechanical response gain".

[0059] The feedback control unit in the embodiment of the present invention is used to adaptively adjust the actual pressure force according to the signal transmitted by the state analysis unit after the pressure force distribution optimization unit completes the calculation of the target pressure at each sensor position, so as to meet the patient's pressure requirements in a static state and during instantaneous movement, thereby realizing closed-loop control of the pressure force deviation and ensuring that the pressure force distribution is within the safe compression range.

[0060] The feedback control unit in the embodiment of the present invention receives the target pressure setting value for each sensor position transmitted by the pressure distribution optimization unit, and maintains the pressure setting value through the proportional-integral-differential control algorithm when the patient is in a static state; when receiving the recovery signal transmitted by the state analysis unit, the feedback control unit immediately adjusts the proportional, integral and differential control coefficients in real time based on the fuzzy control algorithm, and performs pressure regulation operations to adapt to the patient's different physiological conditions. The requirements for pressure regulation.

[0061] The feedback control unit in the embodiment of the present invention adjusts the proportional coefficient, integral coefficient and differential coefficient in real time through a fuzzy control algorithm to adapt to different physiological states of the patient; wherein, when it is detected that the strength of the patient's electromyographic signal exceeds the preset fluctuation threshold of the reference electromyographic signal, the displacement signal exceeds the preset fluctuation range of the reference displacement, or the change amplitude of the acceleration signal exceeds the preset fluctuation range of the reference acceleration, the fuzzy control algorithm increases the proportional coefficient to the increment of the current set value to improve the instantaneous response speed of the system, and at the same time reduces the decrement of the differential coefficient to the current set value, reduces the instantaneous fluctuation of the applied pressure, thereby maintaining a uniform distribution of pressure in a dynamic state and reducing the instantaneous force fluctuation of the puncture point, comprising the following steps:

[0062] Step B1, after receiving the abnormal state signal, the feedback control unit triggers the real-time adjustment mode of the PID control, and the adjusted pressure at the current moment is calculated according to the PID formula, which is:

[0063]

[0064] Among them, F t is the adjusted pressure at the current moment, F base is the initial set pressure, K p , K i and K d are the proportional, integral and differential coefficients respectively, and e is the pressure force error;

[0065] Step B2: When the state evaluation value exceeds the set threshold, the fuzzy control algorithm fuzzifies the electromyographic signal, displacement signal and acceleration signal into three levels of "high", "medium" and "low" according to the deviation of each signal. The PID parameters are further optimized through fuzzy rules, including that when all signals are "low", the system keeps the current set values ​​of the proportional, integral and differential coefficients unchanged to maintain basic stability of the pressure; when any two signals are "low" and the remaining one signal is "medium", the system increases the proportional coefficient to 5% of the current set value to ensure the sensitivity of pressure regulation and adapt to slighter physiological changes; when any one signal is "high" and the other two signals are "low", the system increases the proportional coefficient to 10% of the current set value and reduces the differential coefficient to 5% of the set value to enhance the response to slight changes and reduce instantaneous fluctuations in pressure; when any two signals are "medium" and the remaining one signal is "low", the system increases the proportional coefficient to 10% of the current set value to achieve a smaller pressure response and adapt to moderate changes in physiological state; when any two signals are "high" and the remaining one signal is "low", the system increases the proportional coefficient to 15% of the current set value. And reduce the differential coefficient to 10% of the set value to reduce instantaneous pressure fluctuations when responding to dynamic changes; when any two signals are "high" and the remaining one signal is "medium", the system increases the proportional coefficient to 20% of the current set value and reduces the differential coefficient to 10% of the set value to reduce instantaneous fluctuations while adapting to drastic changes; when all signals are "medium", the system increases the proportional coefficient to 15% of the current set value and appropriately reduces the differential coefficient to 10% of the set value to achieve a moderate pressure response speed; when any one signal is "medium" and the other two signals are "high", the system increases the proportional coefficient to 25% of the current set value and reduces the differential coefficient to 15% of the set value to achieve fast response and pressure balance under strong dynamic conditions; when all signals are "high", the system increases the proportional coefficient to 30% of the current set value and reduces the differential coefficient to 20% of the set value to achieve fast pressure response and system stability under sudden dynamic conditions;

[0066] Step B3, after the fuzzy control algorithm is defuzzified, specific proportional parameter, integral parameter and differential parameter values ​​are obtained; at this time, the PID control parameters can more accurately adapt to the patient's current physiological state and meet dynamic needs;

[0067] Step B4, applying the updated PID parameters to adjust the pressure in real time to ensure that the pressure feedback control matches the patient's dynamic state to meet the rapid response requirements of instantaneous actions;

[0068] Step B5, when it is detected that the electromyography and acceleration signals are restored to the reference range, the system restores the PID parameters to the initial setting values ​​to ensure the stability of the pressure in a static state and avoid excessive adjustment that affects the patient's comfort.

[0069] The state analysis unit in the embodiment of the present invention is used to analyze the patient's electromyographic signal, displacement signal and acceleration signal, calculate evaluation values ​​to identify the patient's static state and instantaneous movement, and send a signal to the feedback control unit when the state changes.

[0070] The state analysis unit in the embodiment of the present invention is used to monitor and analyze the patient's electromyographic signal, displacement signal and acceleration signal in real time, and judge the patient's physiological state by calculating the state evaluation value; wherein the calculation formula of the state evaluation value is:

[0071] R=α·|M-M0|+β·|V-V0|+γ·|A-A0|;

[0072] Where M is the real-time EMG signal, M0 is the reference EMG signal, V is the real-time displacement signal, V0 is the reference displacement signal, A is the real-time acceleration signal, A0 is the reference acceleration signal, and parameters α, β, and γ are the weight coefficients of the EMG signal, displacement signal, and acceleration signal, respectively.

[0073] In the embodiment of the present invention, when the state evaluation value exceeds the preset instantaneous action threshold and the instantaneous change amplitude of the acceleration signal reaches a specific increment, the state analysis unit sends an instantaneous action trigger signal to the instantaneous response module; when the state evaluation value returns to the resting threshold range, the state analysis unit sends a restoring signal to the feedback control unit, including the following steps:

[0074] Step C1, in the initial static state of the patient, the system collects and sets the reference value of the electromyographic signal, the reference value of the displacement signal and the reference value of the acceleration signal, which are used as the reference range of the electromyographic signal, the displacement signal and the acceleration signal, respectively, as the basis for subsequent monitoring and judgment;

[0075] Step C2, continuously collecting electromyographic signal data, comparing it with the reference electromyographic signal, and calculating the electromyographic signal deviation value;

[0076] Step C3: continuously collect displacement signal data, compare it with the reference displacement signal, and calculate the displacement deviation value.

[0077] Step C4, continuously collecting acceleration signal data, and comparing it with the reference acceleration signal to calculate the acceleration deviation value;

[0078] Step C5, when the state evaluation value exceeds the preset instantaneous action threshold, the state analysis unit sends an instantaneous action trigger signal to the instantaneous response module; when the state evaluation value returns to the resting threshold range, the state analysis unit sends a restoring rest signal to the feedback control unit.

[0079] The transient response module is used to monitor and identify the patient's transient movement type and deviation amplitude in real time, and dynamically adjust the pressure during the transient movement according to the movement type and deviation amplitude information, including a movement recognition unit and a pressure adjustment unit.

[0080] The motion recognition unit in the embodiment of the present invention is used to monitor the electromyographic signal, the pressure signal and the acceleration signal in real time, evaluate the deviation amplitude to obtain the change characteristics of the signal, and input the frequency change of the electromyographic signal, the change rate of the pressure signal and the change rate of the acceleration signal into the trained support vector machine model, and classify the input feature data to identify the feature patterns of different instantaneous actions; wherein, the calculation formula for evaluating the deviation amplitude is:

[0081]

[0082] Where M i is the electromyographic signal at the current moment, M0 is the reference electromyographic signal in the resting state, P i is the pressure signal between the tissue around the puncture point and the compression protection device at the current moment, P0 is the reference pressure signal between the tissue around the puncture point and the compression protection device in the resting state, and D i is the deviation magnitude evaluation value.

[0083] The pressure adjustment unit in the embodiment of the present invention dynamically adjusts the pressure based on the action type and deviation amplitude information transmitted by the action recognition unit to balance the pressure impact of the instantaneous action on the puncture point and ensure that the area around the puncture point is supported during the instantaneous action. The pressure adjustment unit calculates the adjusted pressure value according to the following formula:

[0084]

[0085] In the formula, F r is the adjusted pressure, F base is the initial set pressure force, k is the adjustment coefficient related to the action type, which is set according to different action types, D i is the deviation amplitude evaluation value, and n is the adjustment index.

[0086] The real-time monitoring module is used to upload the patient's sensor data through the cloud server, and send warning information to the medical staff's mobile terminal when it detects that the instantaneous action frequency or pressure fluctuation exceeds the preset threshold.

[0087] Example 2

[0088] like Figure 4 The figure shows a mechanical state diagram of a compression protection auxiliary control system for a carotid artery puncture point of the present invention, including a pressure distribution heat map, a displacement vector map, an acceleration time series map and an electromyographic signal waveform map, which comprehensively reflects the mechanical characteristics of the puncture point area under different states.

[0089] The pressure distribution heat map in the embodiment of the present invention reflects the real-time pressure distribution of the puncture point and the surrounding area, and the pressure data range is 0-150mmHg. The pressure at the central puncture point is 120mmHg, which is at a relatively high value; the pressure in the surrounding area is 90mmHg above, 60mmHg below, 70mmHg on the left, and 85mmHg on the right. Through real-time monitoring and heat map display of pressure distribution, the system can accurately identify and mark the pressure concentration area, and guide the dynamic optimization and adjustment of the pressure force accordingly to ensure the stability and safety of the puncture point under high pressure conditions.

[0090] The displacement vector diagram in the embodiment of the present invention captures the displacement range (0-10mm) caused by the patient's position change in real time. The displacement of the upper area is +6mm (upward displacement), the displacement of the lower area is -3mm (downward displacement), the displacement on the left side is +2mm (left displacement), and the displacement on the right side is -5mm (right displacement). The system uses the displacement icons corresponding to the length and direction of the arrows to show the possible impact of changes in position in various directions on the puncture point area. By identifying these position displacement data, the system can adjust the pressure in real time when the position changes, avoid the pressure at the puncture point from being unbalanced due to changes in position, and ensure the continuity of protection.

[0091] The acceleration time series diagram in the embodiment of the present invention shows the acceleration change trend of the puncture point area, which is used to identify the mechanical impact of sudden movements. The acceleration data fluctuates slightly in the resting state, ranging from 0-0.5m / s 2 , indicating that the acceleration is relatively stable at rest. During coughing, the acceleration rises to 3.5m / s 2 , lasting about 0.3 seconds; when the head turns, the acceleration reaches 1.2m / s 2 , which lasts for about 0.5 seconds. Through real-time monitoring of the acceleration curve changes, the system can identify and classify the patient's sudden movement types, and automatically adjust the pressure distribution according to the intensity of the movement, reducing the instantaneous impact of the movement on the puncture point area, thereby improving the protection effect of the puncture point.

[0092] The electromyographic signal waveform in the embodiment of the present invention shows the amplitude change of muscle activity in the puncture point area. The electromyographic signal range is 0-1000μV, reflecting the intensity of muscle activity under different action states. In the resting state, the electromyographic signal is 50-150μV, with a low amplitude, reflecting smaller muscle activity; during slight movements, the electromyographic signal is 200-400μV, with a medium amplitude, indicating an increase in muscle activity; and during coughing, the electromyographic signal instantaneously reaches 800-1000μV, and the amplitude increases significantly, indicating a stronger muscle contraction. Through real-time monitoring of electromyographic signals, the system can perceive the impact of changes in muscle activity, and finely adjust the pressure according to the intensity of muscle activity during instantaneous movements to reduce the impact of muscle contraction on the puncture point.

[0093] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

[0094] Finally: The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A compression protection auxiliary control system for a carotid artery puncture point, comprising a signal integration module and a real-time monitoring module, characterized in that: It also includes a pressure force optimization control module and a transient response module, wherein the signal integration module is connected to the pressure force optimization control module, the transient response module and the real-time monitoring module respectively, the pressure force optimization control module and the transient response module are bidirectionally connected, and the real-time monitoring module is connected to the pressure force optimization control module and the transient response module respectively; The pressure force optimization module is used to analyze sensor data in real time, dynamically adjust the pressure force distribution during the compression protection process of the carotid stent puncture point, and generate target applied force distribution parameters for each sensor position, including a pressure force distribution optimization unit, a feedback control unit and a state analysis unit, wherein the pressure force distribution optimization unit is used to calculate the target pressure value of each sensor position based on the real-time pressure data of each sensor through the pressure force distribution calculation formula; the feedback control unit is used to adaptively adjust the actual pressure according to the signal transmitted by the state analysis unit after the pressure force distribution optimization unit completes the target pressure calculation of each sensor position, so as to meet the pressure requirements of the patient in a static state and instantaneous action; the state analysis unit is used to analyze the patient's electromyographic signal, displacement signal and acceleration signal, identify the patient's static state and instantaneous action through the state evaluation value, and send a signal to the feedback control unit when the state changes; wherein the pressure force distribution calculation formula is: In the formula, F i is the target pressure at the i-th sensor position, T is the total pressure setting value, C i The real-time pressure value measured by each sensor, K i A compensation parameter that changes according to the patient's real-time status; The instantaneous response module is used to monitor and identify the patient's instantaneous movement type and deviation amplitude in real time, and dynamically adjust the pressure during the instantaneous movement according to the movement type and deviation amplitude information, and includes a movement recognition unit and a pressure adjustment unit.

2. A compression protection auxiliary control system for a carotid artery puncture point according to claim 1, characterized in that: The compensation parameter is dynamically adjusted according to the real-time status change of the patient, and its formula is: K i =G·(1+E i ); Where G is the mechanical response gain coefficient, E i is the normalized value of the electromyographic signal.

3. A compression protection auxiliary control system for a carotid artery puncture point according to claim 1, characterized in that: The feedback control unit receives the target pressure setting value for each sensor position transmitted by the pressure distribution optimization unit, and maintains the pressure setting value through the proportional-integral-differential control algorithm when the patient is in a static state; when receiving the recovery signal transmitted by the state analysis unit, the feedback control unit immediately adjusts the proportional, integral and differential control coefficients in real time based on the fuzzy control algorithm to perform pressure regulation operations.

4. A compression protection auxiliary control system for a carotid artery puncture point according to claim 1 or 3, characterized in that: The feedback control unit adjusts the proportional coefficient, integral coefficient and differential coefficient in real time through a fuzzy control algorithm; wherein, when it is detected that the patient's electromyographic signal intensity exceeds the preset fluctuation threshold of the baseline electromyographic signal, the displacement signal exceeds the preset fluctuation range of the baseline displacement, or the change amplitude of the acceleration signal exceeds the preset fluctuation range of the baseline acceleration, the fuzzy control algorithm increases the proportional coefficient to the increment of the current set value, and reduces the differential coefficient to the decrement of the current set value.

5. A compression protection auxiliary control system for a carotid artery puncture point according to claim 1, characterized in that: The state analysis unit is used to monitor and analyze the patient's electromyographic signal, displacement signal and acceleration signal in real time, and judge the patient's physiological state by calculating the state evaluation value; wherein the calculation formula of the state evaluation value is: R=α·|M-M0|+β·|V-V0|+γ·|A-A0|; Where M is the real-time EMG signal, M0 is the reference EMG signal, V is the real-time displacement signal, V0 is the reference displacement signal, A is the real-time acceleration signal, A0 is the reference acceleration signal, and parameters α, β, and γ are the weight coefficients of the EMG signal, displacement signal, and acceleration signal, respectively.

6. A compression protection auxiliary control system for a carotid artery puncture point according to claim 1 or 5, characterized in that: When the state evaluation value exceeds the preset instantaneous action threshold and the instantaneous change amplitude of the acceleration signal reaches a specific increment, the state analysis unit sends an instantaneous action trigger signal to the instantaneous response module; when the state evaluation value returns to the resting threshold range, the state analysis unit sends a restoring signal to the feedback control unit.

7. A compression protection auxiliary control system for a carotid artery puncture point according to claim 1, characterized in that: The motion recognition unit is used to monitor the electromyographic signal, pressure signal and acceleration signal in real time, evaluate the deviation amplitude, and input the frequency change of the electromyographic signal, the change rate of the pressure signal and the change rate of the acceleration signal into the trained support vector machine model, and classify the input feature data to identify the feature patterns of different instantaneous actions; wherein, the calculation formula for evaluating the deviation amplitude is: Where M i is the electromyographic signal at the current moment, M0 is the reference electromyographic signal in the resting state, P i is the pressure signal at the current moment, P0 is the reference pressure signal in the resting state, D i is the deviation magnitude evaluation value.

8. The compression protection auxiliary control system for carotid artery puncture point according to claim 1, characterized in that: The pressure adjustment unit dynamically adjusts the pressure based on the action type and deviation amplitude information transmitted by the action recognition unit to balance the pressure impact of the instantaneous action on the puncture point and ensure that the area around the puncture point is supported during the instantaneous action. The pressure adjustment unit calculates the adjusted pressure value according to the following formula: In the formula, F r is the adjusted pressure, F base is the initial set pressure force, k is the adjustment coefficient related to the action type, which is set according to different action types, D i is the deviation amplitude evaluation value, and n is the adjustment index.

9. A compression protection auxiliary control system for a carotid artery puncture point according to claim 1, characterized in that: The real-time monitoring module is used to upload the patient's sensor data through the cloud server, and send an early warning message to the mobile terminal of the medical staff when it detects that the instantaneous action frequency or pressure fluctuation exceeds the preset threshold.

10. A compression protection auxiliary control system for a carotid artery puncture point according to claim 1, characterized in that: The signal integration module is used to collect pressure signals, displacement signals, acceleration signals and electromyographic signals of the puncture point and its surrounding areas in real time through sensors, perform noise filtering and signal enhancement on the collected data, and fuse the processed data through multi-channel signal mapping to form a mechanical state diagram, which includes a pressure distribution heat map, an electromyographic signal map, a displacement vector map and an acceleration time series map.

Images