Endoscope real-time pressure monitoring system applied to operation implementation process

Abstract

The invention discloses an endoscope real-time pressure monitoring system applied to an operation implementation process, and relates to the technical field of endoscopic surgeries, and the endoscope real-time pressure monitoring system comprises the following steps: S1, setting endoscope channel pressure detection points and deploying a load sensor array; s2, using load sensor array output to establish a channel pressure response mapping model; s3, constructing an operation area image recognition channel, and extracting an endoscopic operation field structure partition map; s4, performing fusion analysis by using the pressure response mapping model and the structure map; s5, constructing a local dynamic pressure fluctuation field by using the regional pressure distribution map; and S6, establishing an intra-operative operation depth-insertion force-local pressure resistance relation model by using the pressure response distribution matrix. By setting a regional pressure construction method based on composite sensing response mapping and surgical field map fusion, the system has real-time regional recognition and mechanical response sensing capabilities under dynamic operation in an operation, and the main problems of pressure measurement and tissue structure decoupling in the prior art are solved.

Description

Technical Field

[0001] The present invention relates to the technical field of endoscopic surgery, and in particular to an endoscopic real-time pressure monitoring system used in the implementation of a surgery. Background Art

[0002] In recent years, endoscopic surgery has been widely used in the field of minimally invasive treatment, which places higher demands on the precision of intraoperative operations and real-time feedback. Especially when operating in flexible cavities such as the digestive tract and respiratory tract, physicians need to frequently adjust the position of the endoscope to pass through complex channels or perform tissue processing. Due to the high variability of the endoscope insertion path, the intraoperative operating force, the pressure distribution in the cavity, and the tissue stress state are often uncontrollable, which can easily cause tissue damage, perforation, or postoperative complications. Therefore, how to ensure the maneuverability of the endoscope while sensing the pressure state of the surgical field structure in real time and forming an effective feedback mechanism has become one of the key issues in the current research of endoscopic-assisted surgery systems. To this end, it is of great significance to construct an endoscopic real-time pressure monitoring system with channel pressure monitoring, surgical field structure perception, and intelligent feedback capabilities.

[0003] Existing technologies generally employ simple measurement methods based on single-point pressure sensors, combined with manual interpretation of imaging information. These methods lack integrated modeling of the three key components: intraoperative dynamic manipulation, localized stress changes in the cavity, and tissue pressure tolerance. Especially in the highly dynamic intraoperative environment, this inability to couple pressure information with the structural region of the surgical field results in a decoupling of the pressure response signal from tissue location and structural properties, making it impossible to accurately reflect the real-time stress state of the local area. Summary of the Invention

[0004] In view of the deficiencies of the prior art, the present invention provides an endoscopic real-time pressure monitoring system for use in a surgical procedure to solve the problems raised in the above-mentioned background technology.

[0005] To achieve the above object, the present invention provides the following technical solutions: In a first aspect, an embodiment of the present invention provides an endoscopic real-time pressure monitoring system for use during surgery, comprising the following steps: S1, setting of pressure detection points in the endoscope channel and deployment of load sensor array; S2, establishing a channel pressure response mapping model using the load sensor array output; S3, constructing a surgical area image recognition channel to extract the endoscopic surgical field structure partition map; S4. Use the pressure response mapping model and the structural map to perform fusion analysis to obtain the regional pressure distribution map; S5. Use the regional pressure distribution map to construct a local dynamic pressure fluctuation field and obtain a real-time pressure response distribution matrix; S6. Use the pressure response distribution matrix to establish an intraoperative operation depth-insertion force-local pressure resistance relationship model to obtain insertion feedback information.

[0006] To further optimize this technical solution, in step S1, a layout priority function for each point is established, and its function formula is: ; in, : discrete position point number in the endoscope path; is a weighting factor used to balance the relationship between the importance of geometric changes on placement and the sensitivity of tissue contact; : waypoint The curvature at : waypoint The contact sensitivity factor of the corresponding cavity tissue is .

[0007] To further optimize this technical solution, the function formula for calculating the sensitivity factor in step S2 is: ; : The risk weight of the tissue at this point output by the image recognition module indicates the risk level of the tissue's response to stress; : The average force and strain per unit area recorded at this point during the historical advancement process; : Sensitivity gain adjustment parameter, used to adjust the response curvature of the function to the input, set by experience; :Tissue strain influencing factors, Inhibition weight in sensitivity.

[0008] To further optimize this technical solution, the step S1 introduces an adaptive placement threshold function , select all points that meet the priority exceeding the threshold, and the function formula is: ; in, : waypoint The indicator function of whether to deploy sensors in the end, Indicates layout, Indicates skip.

[0009] Further optimize this technical solution, the step S1 constructs a deployment point set : ; The sensor type function According to the regional curvature The segments are set to different types of sensors to achieve differentiated configuration of sensor types.

[0010] To further optimize this technical solution, step S4 uses the following formula for fusion analysis: ; ; ; in, is the pixel in the current frame obtained in step S2 In the moment Corresponding pressure response value; : Belongs to the structure tag A set of pixels; :area the actual area; :area At the moment Average pressure; :area The risk coefficient is obtained by looking up the table; : risk-weighted pressure in region r; :area The indicator function of : Final regional pressure distribution map.

[0011] To further optimize this technical solution, the formula in step S4 includes: spatial projection; The three-dimensional pressure grid is accurately projected onto the current frame plane through mature endoscopic calibration-projection technology to obtain ; Regional points; For each structural area Calculate area average pressure , ensuring that the value represents the overall pressure level of the region rather than a single point peak; risk weighting; Obtained by table lookup , linearly amplify the average pressure to highlight the pressure sensitivity of high-risk structures; Regional splicing; Will Backfill to the corresponding mask to form a pressure distribution map of the entire area , sent to the visualization interface in real time.

[0012] Further optimizing this technical solution, the step S5 is to obtain the regional pressure distribution map obtained in step S4. Based on this, dynamic pressure change analysis in the time dimension is introduced. First, a mature image segmentation algorithm is used to divide the surgical area into Discrete Equivalent grid cells form a discrete grid coordinate set ; Then for each grid point ,in accordance with Extract time window The pressure sequence within ; Then, we use mature time series modeling methods to Perform compression feature extraction; Finally, the dynamic indicators of each grid point extracted above are organized into a matrix form .

[0013] Further optimize this technical solution, step S6 uses the output of step S5 , combined with the insertion depth during actual operation and the insertion force collected by the system ,construct a coupling relationship model between local pressure resistance and operation load during surgery to obtain dynamic feedback information; The model formula is: ; in, : At the moment Lower, local area Operational feedback factor; : The insertion force is collected by a high-precision force sensor integrated into the surgical device or handheld operating unit; : insertion depth; : real-time response intensity of the corresponding area in the pressure response distribution matrix; : Operational action function, representing the joint influence between depth and local response; ; : Indicates the real-time insertion depth; : indicates the tissue number marked in the surgical field structure atlas; : Indicates the structure number The insertion force attenuation coefficient is set according to the structural characteristics; : represents the action correction factor; : Local pressure resistance reference function, which indicates the tolerance of tissue to external pressure under normal conditions; ; : Organization Number The historical average pressure value is obtained based on surgical sample statistics; : Organization Number The standard deviation of , which indicates the dispersion of pressure bearing capacity; : Organization Number The safety tolerance factor is dynamically set according to the type of surgery, the device insertion force range or the doctor's experience; : Structure number, corresponding to the marked area in the surgical field structure atlas.

[0014] To further optimize this technical solution, the analysis process of obtaining the inserted feedback information in step S6 includes: Input collection; Real-time synchronous acquisition system insertion force , Endoscope advancement depth ; Obtain the pressure response matrix at the current time point from step S5 ; Local indicator calculation; Traversal Each unit ; Calculating joint impact ; Call the preset pressure resistance standard of the tissue part ; Feedback indicator generation; Substituting the above results into Calculation formula, calculate the local area ; Output feedback matrix ; Feedback information discrimination; Setting threshold parameters , if the parameter , it is considered as an overpressure area and enters the intraoperative risk reminder module; like , indicating that the current state is close to the physiological limit.

[0015] In a second aspect, an embodiment of the present invention provides a computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: when the computer program instructions are executed by the processor, the steps of an endoscopic real-time pressure monitoring system applied during surgical implementation as described in the first aspect of the present invention are implemented.

[0016] In a third aspect, an embodiment of the present invention provides a computer-readable storage medium having a computer program stored thereon, wherein: when the computer program instructions are executed by a processor, the steps of an endoscopic real-time pressure monitoring system applied during surgical implementation as described in the first aspect of the present invention are implemented.

[0017] Compared with the existing technology, the present invention provides a real-time endoscopic pressure monitoring system for use during surgery, which has the following beneficial effects: This endoscopic real-time pressure monitoring system used in the surgical process, by setting up a regional pressure construction method based on the fusion of composite sensor response mapping and surgical field atlas, can jointly model the composite pressure response data and intraoperative image structure partitioning, generate an intraoperative local pressure space map, and serve as the core input for subsequent insertion force prediction and tissue protection judgment, so that the system has real-time regional recognition and mechanical response perception capabilities under dynamic operations during surgery, solving the main problem of decoupling pressure measurement and tissue structure in the existing technology. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0019] Figure 1 This is a flow chart of a real-time endoscopic pressure monitoring system used in a surgical procedure, as proposed by the present invention; Figure 2 This is a schematic diagram of the flow of using the fusion analysis formula of the endoscopic real-time pressure monitoring system applied during the surgical procedure proposed by the present invention; Figure 3 This is a schematic diagram of the analysis process of the insertion feedback information of the endoscopic real-time pressure monitoring system applied during the operation process proposed by the present invention. DETAILED DESCRIPTION

[0020] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific embodiments of the present invention are described in detail below with reference to the accompanying drawings.

[0021] In the following description, many specific details are set forth to facilitate a full understanding of the present invention. However, the present invention may also be implemented in other ways different from those described herein. Those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0022] Secondly, the term "one embodiment" or "embodiment" herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The phrase "in one embodiment" appearing in various places throughout this specification does not necessarily refer to the same embodiment, nor does it constitute a separate or selective embodiment that is mutually exclusive with other embodiments.

[0023] Example 1:

[0024] Reference Figures 1 to 3 , which is the first embodiment of the present invention, provides an endoscopic real-time pressure monitoring system for use in a surgical procedure, comprising the following steps: S1, setting of pressure detection points in the endoscope channel and deployment of load sensor array; In order to deploy a set of non-uniform sensor arrays on the surface of the endoscope channel, it is necessary to refer to the curvature distribution of the propulsion path, the contact sensitivity assessment of the cavity tissue area, and the distribution intensity of the dynamic load impact area; In step S1, the layout priority function of each point is first established, and its function formula is: ; in, : discrete position point number in the endoscope path; is a weighting factor used to balance the relationship between the importance of geometric changes on placement and the sensitivity of tissue contact; : waypoint The curvature at : waypoint The contact sensitivity factor of the corresponding cavity tissue is ; when , indicating that the tissue area is highly sensitive to endoscopic pressure, that is, even a slight pressure may cause damage; when , indicating that the tissue area is insensitive to pressure, that is, it can withstand a large propulsion force or contact stress; The function formula for calculating the sensitivity factor is: ; : The risk weight of the tissue at this point output by the image recognition module indicates the risk level of the tissue's response to stress; : The average force and strain per unit area recorded at this point during the historical advancement process; : Sensitivity gain adjustment parameter, used to adjust the response curvature of the function to the input, set by experience; :Tissue strain influencing factors, the weight of inhibition in sensitivity; Among them, the tissue strain influencing factor Obtained through: Constructing experimental dataset ; : Organizational category risk level output by the image recognition system; : The average strain record of this point under standard thrust in historical operations; : Real sensitive reactions obtained through pathological post-testing, clinical feedback, etc.; Minimum error fitting Using the formula , through the gradient descent method Perform numerical solutions; Multi-region stratified normalization.

[0025] Secondly, introduce the adaptive placement threshold function , select all points that meet the priority exceeding the threshold, and the function formula is: ; in, : waypoint The indicator function of whether to deploy sensors in the end, Indicates layout, Indicates skip.

[0026] Finally, build the deployment point set : ; The sensor type function According to the regional curvature The segments are set to different types of sensors to achieve differentiated configuration of sensor types.

[0027] The sensor placement analysis process in step S1 includes the following steps: Path construction → curvature calculation → tissue sensitivity estimation → priority function establishment → threshold point selection → construction of deployment point set; Step S1 finally deploys sensors according to the deployment point set.

[0028] Step S1 is different from the existing method of arranging pressure sensor points based on physical intuition or rule experience. It innovatively proposes a point screening mechanism based on a composite response factor function. This mechanism constructs a time-varying response function , integrating the local response intensity, signal stability and environmental disturbance adaptability of the sensor point, to achieve quantitative evaluation and screening of candidate points, and thus output the optimal layout point set Compared with the traditional method of uniformly distributing points or based on a single measurement dimension, this method emphasizes the interactive modeling and targeted deployment between different sensing attributes, and has stronger sensitivity adaptation and redundant coverage control capabilities.

[0029] S2, establishing a channel pressure response mapping model using the load sensor array output; In step S2, a mature multi-channel data synchronization acquisition system is first used to align all sensor data to the same time base according to the sampling frequency. At the same time, the original pressure signal is processed through a Butterworth filter to remove high-frequency pseudo-motion effects. The endoscope path trajectory is then fitted using spline interpolation, and the central axis of the entire channel is restored using sensor position information. Based on this, 3D point cloud interpolation technology is used to construct a 3D mesh structure aligned with the channel geometry, with each node corresponding to a set of sensor data samples. Then use the sensitivity factor in step S1 , the pressure data collected at the same time are modulated in response, and the points with high sensitivity are preferentially reflected in the mapping through the normalized weighted average method, that is, the pressure information of the high-risk tissue area has a higher representation weight in the model; Finally, the sliding window method of time series data is used to construct the pressure response results at multiple moments into a continuous pressure distribution dynamic map. The pressure trend of each time window is predicted using the existing dynamic field interpolation model. Finally, a channel pressure response model with time as the axis is established. The model formula is: ; in, Represents the sensor array at time The multi-channel raw output vector of is the pressure response mapping model function; Represents the transformation operation from the physical coordinate space to the image coordinate space The final calculated Represents the pixels in the current frame In the moment The corresponding pressure response value.

[0030] S3, constructing a surgical area image recognition channel to extract the endoscopic surgical field structure partition map; In step S3, endoscopic images are acquired in real time and standard image enhancement methods, including white balance normalization, CLAHE enhancement, and Gaussian filtering, are used to improve image quality. A mature semantic segmentation model is then used to identify structures in the surgical field, including the intestinal boundary, mucosal folds, and microvascular exposure areas, to generate a structural partition map and complete the standardized output of each frame image and its semantic partition map.

[0031] The atlas output is organized in a time series format, with corresponding structural annotations and region masks provided for each frame to facilitate spatial indexing and historical tracking. It is ultimately uploaded to the backend database in a structured format. The atlas is as follows: ; in, : Endoscopic image frame at time Pixel value of : Structural region segmentation function, using U-Net semantic segmentation neural network; : Area label number; : Belongs to the structure tag A set of pixel points as a structural mask; This output provides the spatial structure information input of the image dimension to step S4.

[0032] S4. Use the pressure response mapping model and the structural map to perform fusion analysis to obtain the regional pressure distribution map; Step S4 uses the following formula to perform fusion analysis: ; ; ; in, :area the actual area; :area At the moment Average pressure; :area The risk coefficient is obtained by looking up the table; : risk-weighted pressure in region r; :area The indicator function of : Final regional pressure distribution map.

[0033] The formula in step S4, when used, includes: spatial projection; The three-dimensional pressure grid is accurately projected onto the current frame plane through the mature endoscope calibration-projection technology (using the known field of view geometry and posture matrix) to obtain ; Regional points; For each structural area Calculate area average pressure , ensuring that the value represents the overall pressure level of the region rather than a single point peak; risk weighting; Obtained by table lookup , linearly amplify the average pressure to highlight the pressure sensitivity of high-risk structures; Regional splicing; Will Backfill to the corresponding mask to form a pressure distribution map of the entire area , sent to the visualization interface in real time.

[0034] Unlike existing methods that typically analyze and manually compare structural images and pressure maps separately, step S4 proposes an interactive dual-channel structure-pressure analysis path. This approach uses the anatomical boundaries defined by the spatial structural atlas of the surgical field as constraints to perform spatial matching and fusion of local pressure response information. This process no longer relies on traditional image masking or static region mapping, but instead constructs a continuously adjustable regional response fusion mechanism to ensure that the output regional pressure distribution map has tissue structure correspondence and dynamic response accuracy, thereby better adapting to the real-time changes in the intraoperative scene.

[0035] S5. Use the regional pressure distribution map to construct a local dynamic pressure fluctuation field and obtain a real-time pressure response distribution matrix; Step S5: The regional pressure distribution map obtained in step S4 Based on this, the dynamic pressure change analysis under the time dimension is introduced. First, the mature image segmentation algorithm (Voronoi region segmentation algorithm) is used to divide the surgical area into Discrete Equivalent grid cells form a discrete grid coordinate set ; Then for each grid point ,in accordance with Extract time window The pressure sequence within ; Then, we use mature time series modeling methods to Perform compression feature extraction; Finally, the dynamic indicators of each grid point extracted above are organized into a matrix form to form: ; in, Extract functions for wavelet features or frequency domain indicators; The final result It serves as the core input for executing tasks such as pressure warning and control judgment in step S6.

[0036] S6. Use the pressure response distribution matrix to establish an intraoperative operation depth-insertion force-local pressure resistance relationship model to obtain insertion feedback information; Step S6 uses the output of step S5 , combined with the insertion depth during actual operation and the insertion force collected by the system ,construct a coupling relationship model between local pressure resistance and operation load during surgery to obtain dynamic feedback information; The model formula is: ; in, : At the moment Lower, local area Operational feedback factor; : The insertion force is collected by a high-precision force sensor integrated into the surgical device or handheld operating unit; : insertion depth; : real-time response intensity of the corresponding area in the pressure response distribution matrix; : Operational action function, representing the joint influence between depth and local response; ; : Indicates the real-time insertion depth; : indicates the tissue number marked in the surgical field structure atlas; : Indicates the structure number The insertion force attenuation coefficient is set according to the structural characteristics; : represents the action correction factor; : Local pressure resistance reference function, which indicates the tolerance of tissue to external pressure under normal conditions; ; : Organization Number The historical average pressure value is obtained based on surgical sample statistics; : Organization Number The standard deviation of , which indicates the dispersion of pressure bearing capacity; : Organization Number The safety tolerance factor is dynamically set according to the type of surgery, device insertion force range or doctor's experience; : Structure number, corresponding to the marked area in the surgical field structure atlas.

[0037] The analysis process of obtaining the insertion feedback information in step S6 includes: Input collection: Real-time synchronous acquisition system insertion force , Endoscope advancement depth ; Obtain the pressure response matrix at the current time point from step S5 ; Local indicator calculation: Traversal Each unit ; Calculating joint impact ; Call the preset pressure resistance standard of the tissue part ; Feedback indicator generation: Substituting the above results into Calculation formula, calculate the local area ; Output feedback matrix ; Feedback information identification: Setting threshold parameters , if the parameter , it is considered as an overpressure area and enters the intraoperative risk reminder module; like , indicating that the current state is close to the physiological limit.

[0038] Threshold parameter It is not fixed and can be adjusted according to the surgical scenario, instrument type, tissue category (number ) and the doctor's operating style for dynamic setting; For structurally stable and highly expansible tissues (such as the gastric mucosa): ; For vulnerable tissues (eg, intestinal wall, bile duct): ; For high-risk areas during surgery (such as anastomosis and lesion areas): , and cooperate to reduce the upper limit of instrument insertion force.

[0039] Step S6 establishes a cross-modal coupled feedback inference mechanism, breaking the limitations of traditional models that align insertion force with insertion depth and ignore the physical state of local tissue. This method models the local pressure resistance state in conjunction with real-time operational data, enabling the system to dynamically adjust feedback information and predict possible risky behaviors based on the current tissue state, rather than relying on static rules or preset response intervals. This mechanism provides more adaptive intraoperative decision support and enhances the system's feedback accuracy in complex anatomical structures.

[0040] Example 2:

[0041] This embodiment also provides a computer device, which is suitable for an endoscopic real-time pressure monitoring system used in the implementation of a surgical procedure, and includes a memory and a processor; the memory is used to store computer-executable instructions, and the processor is used to execute computer-executable instructions to implement a real-time endoscopic pressure monitoring system used in the implementation of a surgical procedure as proposed in the above embodiment.

[0042] This embodiment further provides a storage medium having a computer program stored thereon. When the program is executed by a processor, the system for real-time endoscopic pressure monitoring applied during surgery as proposed in the above embodiment is implemented.

[0043] The computer device may be a terminal, comprising a processor, memory, a communication interface, a display, and an input device connected via a system bus. The processor provides computing and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores an operating system and computer programs. The internal memory provides an environment for the operating system and computer programs stored in the non-volatile storage media. The communication interface of the computer device is used to communicate with external terminals via wired or wireless communication. Wireless communication may be achieved via Wi-Fi, a carrier network, NFC (near-field communication), or other technologies. The display of the computer device may be a liquid crystal display or an electronic ink display. The input device may be a touchscreen overlay on the display, buttons, a trackball, or a touchpad on the computer device housing, or an external keyboard, touchpad, or mouse.

[0044] If a function is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the portion that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for causing a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the various embodiments of the method of the present invention. The aforementioned storage medium includes various media that can store program code, such as USB flash drives, mobile hard drives, read-only memories (ROMs), random access memories (RAMs), magnetic disks, or optical disks.

[0045] The logic and / or steps represented in the flowcharts or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing the logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (e.g., a computer-based system, a system including a processor, or other system that can fetch and execute instructions from an instruction execution system, apparatus, or device). For purposes of this specification, a "computer-readable medium" can be any device that can contain, store, communicate, propagate, or transport a program for use by, or in conjunction with, an instruction execution system, apparatus, or device.

[0046] More specific examples (a non-exhaustive list) of computer-readable media include the following: an electrical connection with one or more wires (electronic devices), a portable computer disk cartridge (magnetic devices), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), a fiber optic device, and a portable compact disc read-only memory (CDROM). In addition, the computer-readable medium may even be paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium and then editing, interpreting, or processing it in another suitable manner as necessary, and then storing it in a computer memory.

[0047] It should be understood that various parts of the present invention can be implemented using hardware, software, firmware, or a combination thereof. In the above-described embodiments, multiple steps or methods can be implemented using software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented using hardware, as in another embodiment, any one of the following technologies known in the art or a combination thereof can be used: a discrete logic circuit having logic gate circuits for implementing logic functions on data signals, an application-specific integrated circuit having suitable combinational logic gate circuits, a programmable gate array (PGA), a field-programmable gate array (FPGA), etc.

[0048] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A real-time pressure monitoring system for endoscopes used in surgical procedures, characterized in that: The following steps are involved: S1, setting of pressure detection points in the endoscope channel and deployment of load sensor array; S2, establishing a channel pressure response mapping model using the load sensor array output; S3, constructing a surgical area image recognition channel to extract the endoscopic surgical field structure partition map; S4. Use the pressure response mapping model and the structural map to perform fusion analysis to obtain the regional pressure distribution map; S5. Use the regional pressure distribution map to construct a local dynamic pressure fluctuation field and obtain a real-time pressure response distribution matrix; S6. Use the pressure response distribution matrix to establish an intraoperative operation depth-insertion force-local pressure resistance relationship model to obtain insertion feedback information.

2. The real-time endoscopic pressure monitoring system used in surgical procedures according to claim 1, characterized in that: In step S1, a layout priority function for each point is established, and its function formula is: ； in, : discrete position point number in the endoscope path; is a weighting factor used to balance the relationship between the importance of geometric changes on placement and the sensitivity of tissue contact; : waypoint The curvature at : waypoint The contact sensitivity factor of the corresponding cavity tissue is .

3. The real-time pressure monitoring system for endoscopes used in surgical procedures according to claim 2, characterized in that: The function formula for calculating the sensitivity factor in step S2 is: ； : The risk weight of the tissue at this point output by the image recognition module indicates the risk level of the tissue's response to stress; : The average force and strain per unit area recorded at this point during the historical advancement process; : Sensitivity gain adjustment parameter, used to adjust the response curvature of the function to the input, set by experience; :Tissue strain influencing factors, Inhibition weight in sensitivity.

4. The real-time endoscopic pressure monitoring system used in surgical procedures according to claim 2, characterized in that: The step S1 introduces the adaptive placement threshold function , select all points that meet the priority exceeding the threshold, and the function formula is: ； in, : waypoint The indicator function of whether to deploy sensors in the end, Indicates layout, Indicates skip.

5. The real-time endoscopic pressure monitoring system used in a surgical procedure according to claim 2, characterized in that: The step S1 constructs a deployment point set : ； The sensor type function According to the regional curvature The segments are set to different types of sensors to achieve differentiated configuration of sensor types.

6. The real-time pressure monitoring system for endoscopes used in surgical procedures according to claim 1, characterized in that: The step S4 uses the following formula to perform fusion analysis: ； ； ； in, is the pixel in the current frame obtained in step S2 In the moment Corresponding pressure response value; : Belongs to the structure tag A set of pixels; :area the actual area; :area At the moment Average pressure; :area The risk coefficient is obtained by looking up the table; : risk-weighted pressure in region r; :area The indicator function of : Final regional pressure distribution map.

7. The real-time pressure monitoring system for endoscopes used in surgical procedures according to claim 6, characterized in that: The formula in step S4 includes: spatial projection; The three-dimensional pressure grid is accurately projected onto the current frame plane through mature endoscopic calibration-projection technology to obtain ; Regional points; For each structural area Calculate area average pressure , ensuring that the value represents the overall pressure level of the region rather than a single point peak; risk weighting; Obtained by table lookup , linearly amplify the average pressure to highlight the pressure sensitivity of high-risk structures; Regional splicing; Will Backfill to the corresponding mask to form a pressure distribution map of the entire area , sent to the visualization interface in real time.

8. The real-time pressure monitoring system for endoscopes used in surgical procedures according to claim 1, characterized in that: Step S5 is the regional pressure distribution map obtained in step S4. Based on this, dynamic pressure change analysis in the time dimension is introduced. First, a mature image segmentation algorithm is used to divide the surgical area into Discrete Equivalent grid cells form a discrete grid coordinate set ; Then for each grid point ,in accordance with Extract time window The pressure sequence within ; Then, we use mature time series modeling methods to Perform compression feature extraction; Finally, the dynamic indicators of each grid point extracted above are organized into a matrix form .

9. The real-time endoscopic pressure monitoring system used in a surgical procedure according to claim 1, characterized in that: The step S6 uses the output of step S5 , combined with the insertion depth during actual operation and the insertion force collected by the system ,construct a coupling relationship model between local pressure resistance and operation load during surgery to obtain dynamic feedback information; The model formula is: ; in, : At the moment Lower, local area Operational feedback factor; : The insertion force is collected by a high-precision force sensor integrated into the surgical device or handheld operating unit; : insertion depth; : real-time response intensity of the corresponding area in the pressure response distribution matrix; : Operational action function, representing the joint influence between depth and local response; ； : Indicates the real-time insertion depth; : indicates the tissue number marked in the surgical field structure atlas; : Indicates the structure number The insertion force attenuation coefficient is set according to the structural characteristics; : represents the action correction factor; : Local pressure resistance reference function, which indicates the tolerance of tissue to external pressure under normal conditions; ； : Organization Number The historical average pressure value is obtained based on surgical sample statistics; : Organization Number The standard deviation of , which indicates the dispersion of pressure bearing capacity; : Organization Number The safety tolerance factor is dynamically set according to the type of surgery, the device insertion force range or the doctor's experience; : Structure number, corresponding to the marked area in the surgical field structure atlas.

10. The real-time endoscopic pressure monitoring system used in a surgical procedure according to claim 9, characterized in that: The analysis process of obtaining the insertion feedback information in step S6 includes: Input collection; Real-time synchronous acquisition system insertion force , Endoscope advancement depth ; Obtain the pressure response matrix at the current time point from step S5 ; Local indicator calculation; Traversal Each unit ; Calculating joint impact ; Call the preset pressure resistance standard of the tissue part ; Feedback indicator generation; Substituting the above results into Calculation formula, calculate the local area ; Output feedback matrix ; Feedback information discrimination; Setting threshold parameters , if the parameter , it is considered as an overpressure area and enters the intraoperative risk reminder module; like , indicating that the current state is close to the physiological limit.

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