Anesthesia puncture pressure self-adaptive regulation method and system based on tissue hardness feedback

Abstract

This invention relates to the field of medical device control technology, and discloses a method and system for adaptive control of anesthesia puncture pressure based on tissue stiffness feedback. The method controls a fluid drive unit to operate in microcycles, dividing each microcycle into an active loading segment and a passive relaxation segment. In the active loading segment, pressure peak value and rise rate indices characterizing tissue stiffness are extracted, and a heterogeneity factor is calculated. In the passive relaxation segment, pressure decay indices characterizing tissue permeability are extracted. A multidimensional state vector is constructed by fusing stiffness and permeability characteristics to determine the physical condition. Based on the determined physical condition, the control target is retrieved, and execution parameters such as the duration of the active loading segment in the next cycle are dynamically adjusted using a closed-loop controller. By time-divisionally detecting the solid and fluid dynamic properties of the tissue, dense tissue and obstructive conditions are effectively distinguished, achieving real-time adaptive matching of injection parameters and tissue characteristics, thus reducing the risk of tissue damage while ensuring drug penetration efficiency.

Description

Technical Field

[0001] This invention relates to the field of medical device control technology, specifically to an adaptive control method and system for anesthesia puncture pressure based on tissue stiffness feedback. Background Technology

[0002] Clinical anesthesia procedures typically require the precise injection of medications around specific nerve plexuses or into interstitial spaces. Traditional injection techniques rely heavily on the operator's tactile feedback, using changes in resistance during syringe injection to determine tissue texture and needle tip position. This method is limited by the operator's individual experience and struggles to maintain consistent injection rates. To improve the controllability and stability of the injection process, electrically assisted injection devices have been applied in clinical practice. These devices typically employ a motor-driven mechanism to continuously inject medications into human tissue according to a preset constant flow rate or constant pressure mode.

[0003] Human tissue structures are diverse, with significant differences in tissue density across different areas, leading to non-linear dynamic changes in fluid resistance during injection. Most existing electric injection control logics rely on monitoring a single real-time pressure value. When an increase in tubing pressure is detected, logic that simply depends on pressure thresholds struggles to effectively distinguish whether the pressure increase is caused by the inherent high flow resistance of dense tissue or by abnormal conditions such as needle tip contact with bone or tubing blockage. This limitation in recognizing physical conditions may cause the equipment to trigger unnecessary alarms and halt operation when pressure reaches safety thresholds during injection into dense tissue, affecting operational continuity.

[0004] Biological soft tissues exhibit viscoelastic characteristics, with tissues of varying hardness exhibiting different levels of compliance to fluid volume expansion. Fluid diffusion resistance is lower in loosely textured tissues, while fluid penetration rates are relatively slower in dense tissues. Existing constant-rate injection modes lack dynamic adjustment mechanisms tailored to tissue compliance. Maintaining the same injection parameters in dense tissues as in loose tissues can easily lead to rapid pressure accumulation within local tissue interstitial spaces. If the injection parameters do not match the tissue's physical tolerance, localized high pressure may exceed the tissue's yield limit, posing a risk of mechanical damage to the tissue's microstructure. Current technologies still have room for improvement in adaptively matching injection parameters based on real-time tissue characteristics. Summary of the Invention

[0005] To address the shortcomings of existing technologies, this invention provides an adaptive control method and system for anesthesia puncture pressure based on tissue stiffness feedback. This solves the problems of existing constant-rate injection technology, which cannot sense tissue physical characteristics in real time, has difficulty distinguishing between high impedance in dense tissue and tubing blockage, leading to mechanical damage to tissues or frequent false alarms caused by excessive injection pressure in dense tissues, and cannot dynamically match the optimal injection parameters according to differences in tissue compliance.

[0006] To achieve the above objectives, the present invention is implemented through the following technical solution: an adaptive control method for anesthesia puncture pressure based on tissue stiffness feedback, comprising a method that discretizes the continuous fluid injection process into several control microcycles including active loading segments and passive relaxation segments, and utilizes the intermittent action of the fluid drive unit to achieve periodic detection of tissue mechanical properties and closed-loop control of injection parameters.

[0007] Specifically, the method includes generating micro-periodic pulse drives. A central control unit controls the fluid drive unit to operate in discrete control micro-cycles, each of which is sequentially divided into an active loading phase for performing fluid injection and a passive relaxation phase for ceasing external work. In the active loading phase, the fluid drive unit propels fluid at a preset flow rate to establish a positive pressure gradient within the tubing; in the passive relaxation phase, the fluid drive unit maintains a locked position, ensuring that the injection system tubing and the human tissue form a closed-volume system, facilitating observation of the natural pressure decay process.

[0008] The method includes extracting stiffness characteristics of the actively loaded segment. Fluid pressure data is collected during the actively loaded segment, and the peak pressure index characterizing the instantaneous puncture resistance of the tissue is determined by screening for the maximum pressure value. Simultaneously, a linear pressure-time growth model is established for the pressure data sequence within this segment, and the slope of this model is extracted as the dynamic puncture stiffness characterizing the tissue's bulk elastic modulus. Further, the root mean square error of the residuals of the actual collected pressure data points relative to the linear growth model is calculated and used as a tissue heterogeneity factor to quantify the degree of nonlinear fluctuation during the pressure rise process, thereby assessing the homogeneity of the internal tissue structure.

[0009] The method includes extracting the permeation characteristics of the passive relaxation phase. During the passive relaxation phase, a data sequence of fluid pressure naturally decaying over time is collected. By fitting the data sequence to an exponential decay model or calculating the average pressure drop per unit time, a pressure relaxation decay index characterizing the tissue's fluid conductivity is obtained. The magnitude of this index directly reflects the fluid permeation and diffusion rate in the porous medium of the tissue, where a high decay value corresponds to loose tissue, a low decay value corresponds to dense tissue, and a decay value approaching zero corresponds to a blocked condition.

[0010] The method includes condition determination. The dynamic puncture stiffness, pressure relaxation attenuation index, and tissue heterogeneity factor are fused to construct a multi-dimensional state vector, and this vector is classified into specific physical conditions according to a preset mapping rule. The mapping rule includes: when low dynamic puncture stiffness and medium-to-high pressure relaxation attenuation index are detected, it is determined to be a normal tissue zone condition; when high dynamic puncture stiffness and low pressure relaxation attenuation index are detected, it is determined to be a dense tissue zone condition; when high dynamic puncture stiffness and pressure relaxation attenuation index approaching zero are detected, it is determined to be a blockage alarm zone condition.

[0011] The method includes implementing adaptive feedback control. Based on the determined physical conditions, a control target containing an upper and lower target pressure limit is obtained from a preset control strategy mapping table. By calculating the deviation between the current cycle's peak pressure index and the control target, a controller algorithm is used to determine the adjustment amount of the execution parameters for the next control micro-cycle. Specifically, the adjustment logic is as follows: if the current pressure is lower than the target lower limit, the duration of the active loading segment in the next micro-cycle is increased to increase the single pulse injection volume; if the current pressure is higher than the target upper limit, the duration of the active loading segment in the next micro-cycle is decreased to reduce the single pulse injection volume. Furthermore, fluid pressure is monitored in real time throughout the process. Once the pressure exceeds the absolute safe pressure threshold, the fluid drive unit output is immediately interrupted and an alarm is triggered. This safety mechanism has the highest execution priority.

[0012] The second aspect of the present invention provides an anesthesia puncture pressure adaptive control system based on tissue stiffness feedback, which mainly consists of a pressure sensing module, a fluid drive module, a central control module and a user interaction module.

[0013] The pressure sensing module is installed on the connecting tube of the puncture needle and is used to convert the analog pressure signal during the injection process into a digital pressure sequence at a preset sampling frequency and transmit it to the central control module.

[0014] The fluid drive module is electrically connected to the central control module and is configured to perform fluid injection in a pulse manner in response to control commands. It also has the function of locking the mechanical position by maintaining the motor torque during the passive relaxation phase.

[0015] The central control module establishes data communication connections with the pressure sensing module, the fluid drive module, and the user interaction module, respectively. This module is configured to execute the method described in the first aspect above, specifically responsible for generating micro-period timing sequences, processing pressure data to extract stiffness characteristics, heterogeneity factors, and permeability characteristics, determining physical operating conditions through multi-dimensional feature space mapping, and dynamically updating the pulse control parameters sent to the fluid drive module based on deviation feedback.

[0016] The user interaction module is used to send control commands to the central control module and receive the physical operating status and real-time pressure values ​​output by the central control module for visual display.

[0017] This invention provides a method and system for adaptive control of anesthesia puncture pressure based on tissue stiffness feedback. It has the following beneficial effects:

[0018] 1. This invention achieves time-division detection of the solid mechanical and fluid dynamic properties of tissues by constructing a control microcycle that includes an active loading segment and a passive relaxation segment. Compared to traditional methods that rely solely on the magnitude of pressure values, this invention can effectively distinguish between high pressure generated by dense tissues and high pressure generated by pipeline blockage by utilizing the pressure decay characteristics of the passive relaxation segment. This solves the technical problem that relying solely on pressure thresholds cannot accurately identify the physical conditions of the needle tip, significantly improving the accuracy of identifying complex tissue environments.

[0019] 2. This invention establishes a mapping relationship between tissue physical conditions and control objectives, and performs adaptive adjustment of execution parameters based on pressure feedback. The system can dynamically adjust the duration of the active loading segment according to the identified tissue type, maintaining low-pressure injection in loose tissues to reduce physical stimulation, and appropriately increasing driving capacity in dense tissues to ensure effective drug penetration. This control mechanism achieves real-time matching of injection parameters and tissue characteristics, effectively avoiding the risk of tissue mechanical damage caused by pressure overload while ensuring drug diffusion efficiency.

[0020] 3. This invention quantifies the degree of dispersion of the pressure rise process relative to the linear model by introducing a heterogeneity factor during stiffness feature extraction. This feature can effectively identify heterogeneous structures such as calcifications, fibrous nodules, or microcavities along the puncture path, avoiding misjudgments of operating conditions caused by sudden changes in local resistance, improving the ability of the multidimensional feature space to describe complex lesions, and enhancing the stability of the system under non-ideal clinical operating conditions. Attached Figure Description

[0021] Figure 1 This is a flowchart of the method of the present invention;

[0022] Figure 2 This is a schematic diagram of the pulse drug injection timing principle of the fluid drive unit of the present invention;

[0023] Figure 3 This is a schematic diagram of the pressure waveform timing and feature extraction logic within a single control microcycle of the present invention;

[0024] Figure 4 This is a schematic diagram of the passive relaxation stage pressure data processing of the present invention;

[0025] Figure 5This is a schematic diagram of the spatial mapping of tissue state features according to the present invention;

[0026] Figure 6 This is a schematic diagram of the adaptive control closed-loop logic of the present invention;

[0027] Figure 7 This is a system framework diagram of the present invention. Detailed Implementation

[0028] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0029] See attached document Figure 1 , Figure 1 This is a schematic flowchart of an anesthesia puncture pressure adaptive control method based on tissue stiffness feedback according to an embodiment of the present invention. The present invention provides an anesthesia puncture pressure adaptive control method based on tissue stiffness feedback, comprising the following steps:

[0030] S100, generating micro-cycle pulse drive: The central control unit controls the fluid drive unit to operate in discrete control micro-cycles. Each control micro-cycle is divided into an active loading segment and a passive relaxation segment in terms of timing. In the active loading segment, the drive motor pushes the fluid at a preset flow rate. In the passive relaxation segment, the drive motor stops doing work on the fluid.

[0031] S200, extracting the stiffness characteristics of the active loading section: In the active loading section, the pressure sensing unit collects needle tail pressure data, and the central control unit calculates the pressure peak index characterizing the instantaneous puncture resistance of the tissue and the pressure climb rate index characterizing the elastic modulus of the tissue based on the pressure rise trajectory.

[0032] S300, extracting the permeability characteristics of the passive relaxation phase: In the passive relaxation phase, the central control unit collects the data sequence of pressure decaying naturally over time and calculates the pressure relaxation decay index, which characterizes the tissue fluid conduction capacity.

[0033] S400, constructing a fluid-structure interaction state space and determining the working condition: The central control unit integrates stiffness characteristics and permeability characteristics to construct a multi-dimensional state vector and maps the current puncture state into physical working conditions including loose tissue area, permeable dense area and blocked non-permeable area.

[0034] S500 performs adaptive feedback control: based on the determined physical conditions, the central control unit dynamically adjusts the flow rate of the active loading section and the pause time of the passive relaxation section in the next control microcycle. For the blocked non-permeable zone conditions, it performs forced deceleration or shutdown operations.

[0035] The following section will elaborate on each of the above steps in conjunction with specific computational logic and control strategies.

[0036] See attached document Figure 2 , Figure 2 A schematic diagram of the control micro-period timing structure and pressure sampling logic according to an embodiment of the present invention is shown. In step S100, the specific implementation process of generating the micro-period pulse drive includes constructing a discrete time control sequence and synchronously executing data acquisition, including the following steps:

[0037] S101, constructing time-domain discrete control micro-cycles. The central control unit discretizes the continuous drug injection process into several continuously executed control micro-cycles in the time dimension, denoted as the first... One control microcycle is All control microcycles consist of two temporally consecutive physical processes: an active loading phase and a passive relaxation phase. The total duration of a single control microcycle is set to... The duration of the actively loaded segment is The duration of the passive relaxation phase is The three satisfy a linear superposition relationship:

[0038] ;

[0039] Among them, the duration of the actively loaded segment The product of the fluid injection volume and the preset flow rate determines the fluid injection volume in a single microcycle and the duration of the passive relaxation phase. This determines the length of the observation window for the system's observation of the interstitial fluid diffusion effect. These two time parameters are stored as dynamic control variables in the registers of the central control unit and are updated before the start of each cycle based on the feedback from the previous cycle.

[0040] S102 executes the periodic fluid drive logic. (During the active loading phase...) During this period, the central control unit sends a pulse drive signal of a preset frequency to the fluid drive unit. Upon receiving the pulse signal, the stepper motor in the fluid drive unit generates angular displacement, which, through a mechanical transmission mechanism, pushes the syringe piston to form an axial feed motion. This axial feed motion establishes a positive pressure gradient within the tubing, driving the drug solution into the human tissue. In the subsequent passive relaxation phase... During this process, the central control unit stops sending displacement pulse signals and controls the stepper motor to maintain the current electromagnetic locking torque or utilizes the self-locking characteristic of the transmission mechanism to keep the syringe piston in a fixed position. At this time, the injection system tubing and human tissue form a closed volume system, and the pressure changes within the tubing are eliminated from interference from external mechanical work, determined solely by the permeation and diffusion behavior of the fluid in the porous tissue medium. The microstepping drive and torque holding control of the stepper motor are well-known technologies to those skilled in the art and will not be described in detail here.

[0041] S103 synchronously acquires discrete pressure sequences. During the execution of the control microcycle, the pressure sensing unit operates at a constant sampling frequency. The hydrostatic pressure at the needle tip is continuously acquired. The central control unit reads the analog voltage signal through an analog-to-digital converter interface and converts it into a digitized discrete pressure sequence. ,in is the natural ordinal index of the sampling point. For the In a control micro-cycle, the system extracts pressure data within the corresponding time window based on the timestamp, generating a current cycle pressure sequence that includes pressure increase data during the loading phase and pressure decrease data during the relaxation phase. Each data point in the cycle pressure sequence is synchronously mapped to the motion state of the fluid drive unit on the time axis, thereby converting the continuous physical pressure waveform into a digital signal sequence that can be used by the microprocessor for feature calculations.

[0042] See attached document Figure 3 , Figure 3 The diagram illustrates the timing sequence and feature extraction logic of the pressure waveform within a single control microcycle. In step S200, the specific implementation process for extracting the stiffness features of the actively loaded segment involves statistical analysis and physical modeling of the discrete pressure sequence, including the following steps:

[0043] S201, Define the effective data analysis window. The central control unit determines the first... The time interval of the active loading segment in a control microcycle. Let the start time of this cycle be... The duration of the continuous injection action of the drive motor is The sampling frequency is The system extracts pressure sampling points within this time window, constructing a length of... A subset of the load segment pressure data, in which The total number of sampling points is calculated as follows: and The product is rounded down.

[0044] S202, Calculate the instantaneous peak pressure index. The central control unit filters the pressure data subset of the loading segment and extracts the item with the largest value as the instantaneous peak pressure for the current cycle. Instantaneous peak pressure physically characterizes the total resistance encountered during fluid injection, which is composed of the static reaction force of the tissue itself and the dynamic flow resistance of the fluid at the tubing and needle tip. This value is the peak pressure index characterizing the instantaneous resistance of tissue puncture.

[0045] S203, Calculate the dynamic puncture stiffness index. To eliminate noise interference from single data points and accurately determine the pressure change trend with injection volume, the system uses the least squares method to perform linear regression analysis on a subset of pressure data from the loading section. The system establishes pressure... Regarding time The linear equation is derived, and the slope of this equation is calculated as the dynamic puncture stiffness. The slope is calculated using the following formula:

[0046] ;

[0047] In the formula, This represents the total number of sampling points involved in the calculation;

[0048] Indicates the sequence index of the sampling point;

[0049] Indicates the first The time value of each sampling point relative to the start time of the period;

[0050] Indicates the first The measured pressure values ​​at each sampling point. Since the fluid drive unit propels the fluid at a preset constant flow rate in the active loading section, the derivative of pressure with respect to time is physically equivalent to the derivative of pressure with respect to the injection volume. Therefore, the calculated slope... It directly reflects the bulk elastic modulus of the receptor tissue. A larger value indicates... This indicates that the tissue is firm and has strong resistance to volume expansion; smaller values... This indicates that the tissue has a loose texture and good compliance. The calculation process specifically quantifies the pressure rise rate index, which characterizes the tissue's elastic modulus.

[0051] S204, Calculate the tissue heterogeneity factor. After obtaining the regression line, the system further calculates the dispersion of the original pressure data points relative to the regression line to assess the homogeneity of the tissue's internal structure. The central control unit calculates the root mean square error of the residuals in the pressure data as the heterogeneity factor. The calculation formula is as follows:

[0052] ;

[0053] In the formula, The intercept of the regression line is calculated using the following formula:

[0054] ;

[0055] In the formula:

[0056] This represents the root mean square error of the residuals, i.e., the heterogeneity factor.

[0057] The intercept of the regression line is represented;

[0058] This indicates the calculated dynamic puncture stiffness;

[0059] This indicates the total number of sampling points within the actively loaded segment;

[0060] The sequence index of the sampling point, from 1 to...

[0061] Indicates the first The time value of each sampling point relative to the start time of the loading segment;

[0062] Indicates the first The measured pressure values ​​at each sampling point.

[0063] This represents the degrees of freedom correction term in statistics. The central control unit will calculate... Compare with the preset homogeneity threshold. If A reading significantly higher than the homogeneity threshold indicates significant nonlinear fluctuations during the pressure rise process. In a clinical physics sense, this fluctuation corresponds to the presence of heterogeneous structures such as calcifications, fibrous nodules, or microcavities along the puncture path, causing abrupt changes in injection resistance. Step S204 provides additional dimensional information beyond stiffness for subsequent identification of complex lesion tissue conditions.

[0064] See attached document Figure 4 , Figure 4 A schematic diagram of passive relaxation segment pressure data processing according to an embodiment of the present invention is shown. In step S300, the specific implementation process of extracting the permeability characteristics of the passive relaxation segment involves analyzing pressure decay data under a closed-volume system. Step S300 aims to quantify the permeability and diffusion capacity of fluids in tissues, and specifically includes the following steps:

[0065] S301, define the relaxation segment data analysis window. The central control unit, based on the timing of the fluid drive unit, in the... Within each control microcycle, the system locks the time interval from the end of the active loading segment to the end of the passive relaxation segment. The system extracts pressure sampling points within this time window to construct a subset of pressure data for the passive relaxation segment. This subset of pressure data for the passive relaxation segment follows the subset of pressure data for the loading segment constructed in S201 in time.

[0066] S302, Calculate the pressure relaxation decay index. To quantitatively assess the tissue's ability to conduct fluids, the central control unit calculates the pressure decay rate within the passive relaxation phase. In one specific implementation, the pressure relaxation decay index is obtained by fitting an exponential decay model to the relaxation phase pressure data. The system establishes pressure... Regarding time The single exponential decay function model:

[0067] ;

[0068] In the formula:

[0069] Indicates the relaxation section Predicted pressure values ​​at any given time;

[0070] This represents the measured pressure value at the start of the relaxation phase, i.e., the pressure value of the first sampling point in the relaxation phase data subset;

[0071] The measured residual pressure value at the end of the relaxation phase is the pressure value of the last sampling point in the relaxation phase data subset, representing the steady-state back pressure after the fluid reaches local diffusion equilibrium within the tissue.

[0072] Indicates the duration since the start of the relaxation phase;

[0073] Represents the natural constant;

[0074] This represents the pressure relaxation attenuation coefficient.

[0075] The central control unit employs nonlinear least squares or other numerical optimization algorithms to solve for parameters that minimize the error between model predictions and actual measurements, based on a subset of collected relaxation-segment pressure data. This parameter It is a pressure relaxation attenuation index that characterizes the tissue's fluid conduction capacity.

[0076] In another alternative simplified implementation, to reduce computational complexity, the pressure relaxation decay index... It can also be approximated by calculating the average rate of change of pressure throughout the entire relaxation period. At this point, It can be directly defined as the difference between the initial and final pressures of the relaxation phase divided by the total duration of the relaxation phase. .

[0077] In a physical sense, this indicator It is positively correlated with the organization's permeability. When A larger value indicates rapid pressure decay, meaning the fluid can quickly diffuse and penetrate within the interstitial spaces, suggesting good fluid conductivity in tissues such as loose adipose or muscle tissue. A smaller value indicates slow pressure decay and impaired fluid permeability, suggesting a dense tissue structure, such as dense fibrous connective tissue. If... If the pressure approaches zero, it indicates that the pressure hardly decreases throughout the relaxation phase, the system is completely blocked, and the fluid cannot penetrate effectively, like a needle tip being blocked by the surface of bone or a completely impermeable lesion.

[0078] Through this step, the present invention introduces the rate of change of pressure over time (permeability) as a new criterion dimension, thereby enabling the differentiation of two high-pressure states with different physical properties: one is high pressure generated by dense tissue, but the drug solution can still slowly permeate; the other is the same high pressure generated by the complete blockage of the needle tip, but the drug solution cannot permeate at all.

[0079] See attached document Figure 5 , Figure 5 This is a schematic diagram of tissue state feature space mapping according to an embodiment of the present invention. In step S400, the system fuses and analyzes multiple physical feature parameters calculated in the preceding steps to achieve accurate determination of the current injection condition, including the following steps:

[0080] S401, Construct a multi-dimensional feature space. The central control unit calculates the dynamic puncture stiffness using the data from step S203. As the first dimension, the pressure relaxation attenuation index calculated in step S302. The second dimension is the tissue heterogeneity factor calculated in step S204. A three-dimensional tissue state feature space is constructed as the third dimension. The first dimension primarily reflects the solid mechanical properties of the tissue (hardness, elasticity), the second dimension primarily reflects the fluid mechanical properties of the tissue (permeability, conductivity), and the third dimension reflects the homogeneity of the internal structure of the tissue. All characteristic parameter combinations calculated using control micro-periods are used. Each of these can be considered a feature vector in three-dimensional space.

[0081] S402, execute operating condition status mapping. The central control unit will map the current operating condition status. The feature vector calculated by each control microcycle is compared with a preset operating condition model to determine the current tissue state of the needle tip. In one specific implementation, the operating condition model can be stored in the non-volatile memory of the central control unit, and its form can be a look-up table (LUT) or a set of nested IF-ELSE conditional statements. The central control unit maps the feature vector to a predefined state partition by looking up the table or executing the conditional statements.

[0082] S403 defines the state partitioning rules. The preset working condition model divides the feature space according to the following rules. Each partition corresponds to a specific injection working condition, and its boundaries are determined by pre-calibrated thresholds based on extensive in vitro experimental data, clinical statistics, or physical model simulations. Clinical studies have shown that the physical properties of different tissues vary significantly. For example, the hardness of normal muscle tissue is typically in the range of 10-20 kPa, while the hardness of some tumor tissues can reach 50-80 kPa. These differences in physical properties directly affect the injection effect; for example, in hard tissues, drug penetration is slower, which may lead to a prolonged onset of action. The state partitioning rules are established based on these objective differences:

[0083] Normal tissue area: Normal tissue areas correspond to lower dynamic puncture stiffness, moderately high pressure relaxation attenuation index, and lower heterogeneity factor. This indicates that the needle tip is located in normal tissue (such as fat or muscle) with relatively loose texture, good fluid conductivity, and homogeneous structure.

[0084] Uniform and dense tissue region: The uniform and dense tissue region corresponds to higher dynamic puncture stiffness, lower pressure relaxation attenuation index and lower heterogeneity factor, indicating that the needle tip is located in a tissue with hard texture, difficult fluid penetration but uniform structure, such as dense fibrous connective tissue.

[0085] Heterogeneous dense tissue regions: Heterogeneous dense tissue regions correspond to higher dynamic puncture stiffness, lower pressure relaxation decay indices, and significantly higher heterogeneity factors. This indicates that the needle tip is located in tissues with high rigidity, poor permeability, and complex internal structures, such as tumor entities containing necrosis, calcification, or fibrosis.

[0086] Vascular puncture area: The vascular puncture area corresponds to extremely low dynamic puncture stiffness and extremely high pressure relaxation attenuation index. It is characterized by pressure that hardly rises or rises and then quickly falls back to an extremely low level, because the circulatory system can quickly remove the injected trace amount of fluid.

[0087] Blockage alarm zone: The blockage alarm zone corresponds to a medium to high range of dynamic puncture stiffness and a pressure relaxation attenuation index approaching zero. This indicates that pressure can be established in the active loading phase, but hardly attenuates in the passive relaxation phase. Physically, this corresponds to a blockage state where the needle tip is blocked by completely impermeable obstacles such as bone, calcifications, or blood clots.

[0088] Through a mapping process executed in real time each cycle, the system achieves continuous dynamic tracking of the injection conditions. This discrimination method, based on the fusion of multi-dimensional features from solid mechanics and fluid mechanics, solves the technical challenge of distinguishing between dense tissue and blocked tubing solely based on pressure magnitude. It further identifies the structural complexity within the tissue, significantly improving the accuracy and safety of condition identification. This method forms the basis for an adaptive matching algorithm between tissue stiffness and injection pressure, providing core technical support for overcoming the limitations of traditional fixed-pressure injection methods.

[0089] See attached document Figure 6 , Figure 6 This is a schematic diagram of adaptive control closed-loop logic according to an embodiment of the present invention. In step S500, the system dynamically adjusts the execution parameters of subsequent control microcycles based on the operating condition determined in S400, forming closed-loop feedback control. Step S500 specifically includes the following steps:

[0090] S501, Associating Status with Control Objectives. The central control unit internally stores a control strategy mapping table, which associates each operating condition defined in step S400 with a specific set of control objectives. These control objectives include target pressure ranges (including the target pressure upper limit). and target pressure lower limit ), safety pressure threshold For example, when the condition is identified as a normal tissue area, the control objective is set to maintain a low injection pressure (e.g., 5-10 kPa) to reduce tissue irritation. When the condition is a dense tissue area, the control objective is adjusted to appropriately increase the injection pressure (e.g., 20-30 kPa) while ensuring safety, to ensure effective drug penetration. When the condition is a blockage alarm area, the control objective is to immediately stop the injection and trigger an alarm.

[0091] S502, executes adaptive parameter adjustment. In the... After the first control microcycle ends, the central control unit retrieves the corresponding control objective from the control strategy mapping table based on the identified operating condition, and calculates and updates the target for the next control microcycle (the first microcycle). The execution parameters are set for each cycle. In one specific implementation, the execution parameter adjustment process can be achieved through a proportional-integral (PI) controller. The PI controller will adjust the peak pressure of the current cycle. The pressure error is calculated by comparing it with the target pressure range, and the adjustment amount of the execution parameters is generated based on the error.

[0092] Adjust the duration of the active loading segment Adjusting the duration of the active loading segment directly affects the injection volume and average flow rate of the next microcycle. The Pl controller calculates the... Each cycle Its adjustment logic is as follows: if the peak pressure of the current cycle... Below the target pressure lower limit The controller will be in the current Based on this, a positive adjustment is added to increase the injection volume per pulse; if the peak pressure is higher than the target pressure limit. The controller will be in the current A negative adjustment is applied on top of this to reduce the injection volume. This incremental adjustment based on pressure feedback is the core execution step for achieving adaptive matching of tissue stiffness and injection pressure.

[0093] Adjust the duration of the passive relaxation phase The length of the passive relaxation phase determines the length of the observation window for tissue penetration. This window can be appropriately extended during the initial injection phase or when the needle tip position changes rapidly. This allows for a more complete pressure decay curve, thereby improving the accuracy of tissue permeability assessment. Once the injection status has stabilized, the infusion time can be appropriately shortened. This is to improve overall injection efficiency while ensuring necessary feedback information.

[0094] 5503, Perform safety monitoring and response. Throughout the control process, the central control unit continuously compares the real-time pressure values ​​with an absolute safe pressure threshold. (e.g., 50 kPa) is compared. This threshold is preset based on clinical safety standards and is designed to prevent tissue damage caused by excessive pressure (e.g., the 0.5% liver capsule rupture rate that manual injection may cause in clinical statistics). This safety monitoring function is implemented through hardware interruption or a high-priority task, with a response priority higher than the PI controller in S502. Once the real-time pressure is detected to exceed this threshold, the central control unit will unconditionally and immediately interrupt the pulse signal output of the fluid drive unit and trigger an audible and visual alarm to prompt operator intervention.

[0095] See attached document Figure 7 , Figure 7This is a system framework diagram of an anesthesia puncture pressure adaptive control system based on tissue stiffness feedback according to an embodiment of the present invention. The system aims to achieve intelligent matching and dynamic adjustment of pressure and flow rate during injection based on real-time sensed tissue physical characteristics. The system includes:

[0096] A pressure sensing module, integrated into the puncture needle or its connecting tubing, is used to monitor fluid pressure in real time during the injection process. In one specific embodiment, the pressure sensing module can be a piezoresistive sensor with a range of 0-100 kPa and an accuracy of ±0.5 kPa, capable of continuously acquiring pressure signals at a sufficiently high sampling frequency (e.g., 1 kHz) and converting analog signals into digital pressure sequences to provide raw data for subsequent feature extraction.

[0097] The fluid drive module is used to precisely inject fluid in a pulsed manner according to control commands. This module typically consists of a stepper motor, a lead screw drive mechanism, and a standard syringe. The central control unit can precisely control the active loading duration and passive relaxation duration within all control microcycles by controlling the pulse frequency and number of the stepper motor, thereby achieving precise control of the fluid injection rate and volume.

[0098] The central control module is used to execute the adaptive control method. This module is typically a microcontroller (MCU) or embedded processor, which contains the program code implementing the method. Specifically, the central control module is configured to perform the following functions:

[0099] Receives real-time digital pressure sequences from the pressure sensing module.

[0100] Based on the action sequence of the fluid drive module, the pressure sequence is divided into data subsets of the active loading segment and the passive relaxation segment.

[0101] The feature extraction process in step S200 calculates the dynamic puncture stiffness index and tissue heterogeneity factor, which characterize the solid mechanical properties of tissue, from the unprocessed pressure data.

[0102] The feature extraction process in step S300 is executed to calculate the pressure relaxation attenuation index, which characterizes the tissue's hydrodynamic properties.

[0103] The working condition mapping process in step S400 involves fusing and analyzing multiple extracted physical features to construct a multidimensional feature vector, which is then compared with a preset state partitioning model to determine the current tissue state of the needle tip in real time, whether it is normal tissue, dense tissue, or blocked.

[0104] The closed-loop feedback control process in step S500 retrieves the corresponding control target (such as the target pressure range) from the preset control strategy mapping table based on the identified tissue state. Then, using algorithms such as a proportional-integral (PI) controller, it automatically calculates and updates the execution parameters of the fluid drive module in the next control micro-cycle, achieving adaptive adjustment of the injection pressure towards the target pressure. Simultaneously, this module also performs independent, high-priority safety monitoring to ensure that the real-time pressure does not exceed the preset absolute safety threshold.

[0105] The user interaction module displays system status and receives commands from the operator. This module can be an LCD screen with several physical buttons, or a touchscreen. It can display the currently measured pressure value, the identified tissue type, the system's operating mode, and any alarm information in real time, and allows the operator to start, pause, or terminate the injection process.

[0106] Through the coordinated operation of the above modules, the puncture needle tip can be transformed into an intelligent probe capable of sensing the softness and permeability of tissue in real time, and automatically adjusting the injection strategy based on this sensing information, thereby ensuring effective drug delivery.

Claims

1. A method for adaptive control of anesthesia puncture pressure based on tissue stiffness feedback, characterized in that, Includes the following steps: S100, generating micro-cycle pulse drive: controlling the fluid drive unit to run in discrete control micro-cycles, dividing each control micro-cycle in time sequence into an active loading segment where the fluid drive unit performs the injection action and a passive relaxation segment where the fluid drive unit stops doing external work; S200, Extract the stiffness characteristics of the active loading section: In the active loading section, collect fluid pressure data, calculate the pressure peak index characterizing the instantaneous puncture resistance of the tissue and the pressure rise rate index characterizing the bulk elastic modulus of the tissue, as stiffness characteristics. S300, Extracting the permeability characteristics of the passive relaxation segment: In the passive relaxation segment, a data sequence of fluid pressure naturally decaying over time is collected, and a pressure relaxation decay index characterizing the tissue fluid conductivity is calculated as a permeability characteristic. S401, Determine working condition: Fuse the stiffness feature and the penetration feature to construct a multi-dimensional state vector, and map the current puncture state to a preset physical working condition; S500 performs adaptive feedback control: based on the determined physical conditions, it dynamically adjusts the execution parameters of the active loading segment or the passive relaxation segment in the next control microcycle.

2. The method for adaptive control of anesthesia puncture pressure based on tissue stiffness feedback according to claim 1, characterized in that, In step S100, the specific process of generating the micro-periodic pulse drive includes: In the active loading section, a pulse drive signal is sent to the fluid drive unit to drive the syringe piston to generate axial feed motion and establish a positive pressure gradient in the pipeline. During the passive relaxation phase, the pulse drive signal is stopped and the torque of the fluid drive unit is locked, so that the position of the syringe piston is kept fixed, and the diffusion behavior of the fluid in the tissue medium is observed by utilizing the pressure change in the tubing.

3. The method for adaptive control of anesthesia puncture pressure based on tissue stiffness feedback according to claim 1, characterized in that, In step S200, the specific process of calculating the pressure rise rate index characterizing the tissue bulk elastic modulus includes: Extract the pressure data sequence within the actively loaded segment; Linear regression analysis was performed on the pressure data sequence to establish a linear growth model of pressure over time; The slope of the linear growth model is extracted and used as the dynamic puncture stiffness to quantify the pressure ramp rate index.

4. The method for adaptive control of anesthesia puncture pressure based on tissue stiffness feedback according to claim 3, characterized in that, Step S200 also includes the step of calculating the tissue heterogeneity factor: Based on the linear growth model, the root mean square error of the residuals of the actual pressure data points collected within the active loading segment relative to the regression line is calculated. The residual mean square error is used as the tissue heterogeneity factor to assess the uniformity of the internal structure of the tissue and as an auxiliary dimension for determining the working condition in step S401.

5. The method for adaptive control of anesthesia puncture pressure based on tissue stiffness feedback according to claim 1, characterized in that, In step S300, the specific process of calculating the pressure relaxation attenuation index characterizing the tissue's fluid conductivity includes: Extract the pressure data sequence within the passive relaxation segment; The pressure data sequence is fitted with an exponential decay model, and the decay coefficient obtained from the fitting is extracted as the pressure relaxation decay index; wherein, the larger the value of the pressure relaxation decay index, the stronger the tissue fluid conduction ability.

6. The method for adaptive control of anesthesia puncture pressure based on tissue stiffness feedback according to claim 1, characterized in that, In step S401, mapping the current puncture state to a preset physical condition specifically includes: Construct a feature space that includes the dynamic puncture stiffness dimension and the pressure relaxation attenuation index dimension. When low dynamic puncture stiffness and medium-to-high pressure relaxation attenuation index are detected, it is determined to be a normal tissue zone condition. When high dynamic puncture stiffness and low pressure relaxation attenuation index are detected, it is determined to be a working condition in a dense tissue area. When high dynamic puncture stiffness and pressure relaxation attenuation index approaching zero are detected, the condition is determined to be in the blockage alarm zone.

7. The method for adaptive control of anesthesia puncture pressure based on tissue stiffness feedback according to claim 1, characterized in that, In step S500, the execution of adaptive feedback control specifically includes: A control strategy mapping table is pre-stored to associate each physical condition with a control objective that includes the target pressure upper limit and the target pressure lower limit; Based on the determined physical conditions, the corresponding control target is determined from the control strategy mapping table; The deviation between the current cycle's peak pressure index and the control target is calculated, and the controller algorithm is used to calculate the adjustment amount of the execution parameters for the next control microcycle.

8. The method for adaptive control of anesthesia puncture pressure based on tissue stiffness feedback according to claim 7, characterized in that, The logic for performing adaptive feedback control includes: If the current cycle's peak pressure index is lower than the target pressure lower limit, a positive adjustment amount is added based on the current active loading segment duration to increase the single pulse injection amount; If the peak pressure index of the current cycle is higher than the target pressure limit, a negative adjustment is applied based on the current active loading segment duration to reduce the injection volume per pulse.

9. The method for adaptive control of anesthesia puncture pressure based on tissue stiffness feedback according to claim 1, characterized in that, The pressure adaptive control method also includes a safety monitoring step: Throughout the entire process from steps S100 to S500, the fluid pressure is monitored in real time. The real-time fluid pressure is compared with a preset absolute safety pressure threshold. Once the real-time fluid pressure is detected to exceed the absolute safety pressure threshold, the output of the fluid drive unit is immediately interrupted and an alarm is triggered. The priority of this interruption operation is higher than that of the adaptive feedback control in step S500.

10. An anesthesia puncture pressure adaptive control system based on tissue stiffness feedback, used to implement the method according to any one of claims 1-9, characterized in that, include: The pressure sensing module is installed on the connecting tube of the puncture needle and is connected to the central control module for signal transmission. It is used to collect real-time fluid pressure data during the injection process and transmit it to the central control module. The fluid drive module is signal-connected to the central control module and is used to receive control commands issued by the central control module to perform fluid injection actions in a pulse manner. The central control module, as the core processing unit, establishes data communication connections with the pressure sensing module, the fluid drive module, and the user interaction module, respectively. The user interaction module is signal-connected to the central control module and is used to send operation commands to the central control module and receive and display the physical operating status output by the central control module.

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