Clysis auxiliary system integrating lubrication and visual catheter

Abstract

The invention relates to the technical field of medical data processing, in particular to a lubrication and visual catheter integrated enema auxiliary system which comprises an automatic focal length adjusting module, a data flow optimizing module, a roughness analyzing module, a propelling track calculating module and a lubricant applying module. According to the invention, the intestinal wall distance is acquired in real time, the focal length parameter of the lens group is adjusted, the image definition is optimized, the image change is analyzed, the compression ratio of the image data is dynamically adjusted, the image data flow is optimized, the data transmission delay and bandwidth occupation are reduced, and the roughness of the intestinal wall surface and the morphological change of the intestinal tract are identified in combination with image analysis. The catheter propelling force parameter is dynamically adjusted, the smoothness and safety of catheter insertion are ensured, the injection amount of the lubricant at multiple positions is calculated, the application of the lubricant is accurately controlled, the visualization effect of enema operation, the operation accuracy and the patient comfort degree are improved, and the diagnosis and treatment process is optimized.

Description

Technical Field

[0001] The invention relates to the technical field of medical data processing, and in particular to an enema auxiliary system integrating lubrication and visual catheter. Background Art

[0002] The field of medical data processing technology includes computer systems for medicine and health management. The core content includes the collection, storage, analysis and visualization of medical information. Medical data processing involves electronic health record management, medical image processing, and medical record data analysis. It aims to improve the readability and availability of medical data, first of all to assist medical decision-making, optimize the diagnosis and treatment process, and improve the level of patient management. It covers physiological parameter collection, computer-aided diagnosis, intelligent image analysis, remote medical monitoring, and clinical decision support. It also realizes accurate management and processing of data through computer algorithms, database management systems, and data interaction protocols.

[0003] Among them, the enema auxiliary system with integrated lubrication and visual catheter adopts an automatic lubricant application mechanism, a fiber optic visual catheter and real-time image transmission to meet the requirements of smooth catheter insertion and visual operation during the enema process. The automatic lubricant application mechanism controls the uniform coating of the lubricant through a micro pump, reducing friction resistance and improving insertion comfort. The fiber optic visual catheter has a built-in micro camera and lighting component, which transmits image signals to the external display terminal through the catheter wall, allowing the operator to observe the front end position of the catheter and the internal situation of the intestine in real time. The real-time image transmission module is based on the data transmission protocol, and transmits the image data to the terminal device by wired or wireless means, ensuring stable transmission and intuitive display of information during the operation.

[0004] In traditional enema-assisted technology, the application of lubricant during enema operation usually relies on manual operation or simple automatic control. The amount of lubricant sprayed cannot be dynamically adjusted according to the real-time friction force of the catheter in the intestine, resulting in uneven lubrication effect, increased friction resistance during catheter insertion, affecting patient comfort, and unable to adjust the lens focal length according to changes in intestinal wall distance, resulting in blurred or distorted images, affecting the operator's accurate judgment of the internal situation of the intestine. The image data stream optimization capability is limited, and the compression ratio cannot be dynamically adjusted according to the pixel displacement and brightness change between adjacent frames, resulting in data transmission delays or excessive bandwidth occupancy, affecting the stable transmission of real-time images, and unable to accurately identify changes in the roughness of the intestinal contact area, resulting in a lack of precision in the adjustment of the catheter advancement force, increasing operational risks and affecting the efficiency and safety of enema operations. Summary of the invention

[0005] The purpose of the present invention is to solve the shortcomings in the prior art and to propose an enema auxiliary system integrating lubrication and visual catheter.

[0006] In order to achieve the above object, the present invention adopts the following technical solution: an enema auxiliary system with integrated lubrication and visual catheter comprises: The focus automatic adjustment module calls the ultrasonic sensor to obtain the intestinal wall distance data in real time and calculates the intestinal wall distance change. By analyzing the relationship between the focus offset and the intestinal wall distance change, the focus parameter of the lens group is adjusted to obtain the focus adjustment parameter. The image data stream optimization module acquires the image frame sequence of the front end of the intestinal catheter in real time based on the focal length adjustment parameter, detects and calculates the pixel displacement and brightness change between adjacent frames, and adjusts the compression ratio of the image data according to the degree of change between adjacent frames to obtain an optimized image data stream; The roughness analysis module obtains the image frame sequence of the intestinal contact area based on the optimized image data stream, detects the brightness gradient change and pixel edge contour density of the contact area between the catheter and the intestinal wall, calculates the pixel density change rate of the contact area, analyzes the surface roughness gradient distribution of the contact area, and obtains the roughness distribution value; The propulsion trajectory calculation module calls the image data based on the roughness distribution value, identifies the morphological changes of the intestine, including contraction and expansion, calculates the changes of intestinal friction and propulsion resistance, adjusts the catheter propulsion force parameter, and obtains the propulsion force parameter; The lubricant intelligent application module calculates the injection amount of the lubricant at multiple positions based on the propulsion force parameter and the real-time friction force of the catheter in multiple intestinal wall areas to obtain the lubricant application parameter.

[0007] As a further scheme of the present invention, the focal length adjustment parameters are specifically the focal length offset correction value, the lens group adjustment coefficient, and the intestinal wall distance change rate; the optimized image data stream includes the pixel displacement calculation results, the brightness change analysis results, and the data compression ratio adjustment value; the roughness distribution value is specifically the contact area pixel density change rate, the friction gradient calculation value, and the intestinal contact pressure distribution data; the propulsion force parameters include the propulsion force adjustment coefficient, the intestinal friction calculation result, and the resistance change trend value; the lubricant application parameters specifically refer to the lubricant injection amount calculation value, the injection position distribution data, and the lubrication coverage range.

[0008] As a further solution of the present invention, the focus automatic adjustment module includes: The ultrasonic data acquisition submodule calls the ultrasonic sensor, monitors the distance between the intestinal wall and the sensor by analyzing the real-time output signal of the sensor, collects the time series data of the intestinal wall distance, and generates a real-time intestinal wall distance data set; The distance change analysis submodule calculates the intestinal wall distance change between consecutive time points based on the intestinal wall real-time distance data set, analyzes the change trend, and obtains intestinal wall distance change data; The focal length parameter adjustment submodule calls the intestinal wall distance change data, analyzes the relationship between the focal length offset and the intestinal wall distance change, and adjusts the focal length parameters of the lens group by calculating the degree of offset, using the formula: ; Calculate the optimal value of focal length adjustment and generate focal length adjustment parameters; in, Represents the focal length adjustment value, and are the maximum and minimum values ​​of the intestinal wall distance, is the intestinal wall distance measured in a single time, is the average intestinal wall distance, is the current lens focal length parameter, is the focal length offset, Represents the index of a single data point in the intestinal wall distance measurement data, Represents the total number of measurements.

[0009] As a further solution of the present invention, the data flow optimization module includes: The image frame sequence acquisition submodule acquires the image frame sequence of the front end of the catheter in the intestine based on the focal length adjustment parameter by receiving the continuous image data stream output by the camera in real time, and generates an image frame data set; The adjacent frame variation calculation submodule analyzes the pixel difference between each pair of adjacent frames based on the image frame data set, calculates the pixel displacement and brightness variation, obtains the inter-frame variation, and generates pixel displacement and brightness variation data; The data compression ratio adjustment submodule analyzes the degree of change between adjacent frames according to the pixel displacement and brightness change data, using the formula: ; Obtaining the optimized compression ratio value and generating an optimized image data stream; in, represents the compression ratio adjustment parameter, Represents the pixel displacement of each frame, Represents the size of the current frame, Represents the brightness change, represents the frame time interval, Represents the total number of frames in the image frame dataset, Represents the index of each frame of data.

[0010] As a further solution of the present invention, the roughness analysis module includes: The image frame acquisition submodule extracts intestinal wall images at multiple time points through the optimized image data stream to obtain an image frame sequence of the intestinal contact area; The brightness gradient analysis submodule detects the brightness gradient change amount of the contact area between the catheter and the intestinal wall based on the image frame sequence of the intestinal contact area, and analyzes the pixel edge contour density of the contact area to obtain the brightness gradient change amount; The roughness gradient calculation submodule compares the correlation between the brightness gradient and the pixel edge contour density according to the brightness gradient change, and adopts the formula: ; Calculate the roughness of multiple locations and generate roughness distribution values; in, represents the friction value at position c, represents the brightness of the image at position c, represents the brightness gradient change at position c, represents the pixel density at position c, represents the edge contour density of the dth pixel at the cth position, represents the average edge contour density at position c, Represents the number of pixel edges at each location.

[0011] As a further solution of the present invention, the propulsion trajectory calculation module includes: The real-time morphology recognition submodule calls the image data based on the roughness distribution value, identifies the contraction and expansion state of the intestine by calculating the contour changes in each frame of the image, marks the regional changes of contraction and expansion, and generates an intestinal morphology change data set; The resistance calculation submodule calculates the intestinal friction and propulsion resistance changes through the intestinal morphology change data set, combined with the brightness gradient and roughness distribution value of the contact area between the catheter and the intestinal wall, and generates friction and resistance data; The propulsion force adjustment submodule is based on the friction and resistance data through the formula: ; Calculate the propulsion force and obtain the propulsion force parameter; in, Represents the driving force, Represents the pixel displacement of each frame, represents the change in friction, represents the current resistance of the catheter, Represents the amount of resistance change to be adjusted, represents the adjusted intestinal friction, Represents the resistance adjustment value required when advancing the catheter.

[0012] As a further solution of the present invention, the lubricant application module comprises: The friction force analysis submodule further calculates the friction force data of the contact area between the catheter and the intestinal wall in the intestine based on the propulsion force parameter and the propulsion force of the catheter at multiple intestinal wall positions to obtain real-time friction force data; The lubricant demand assessment submodule uses the formula based on the real-time friction data: ; Calculate the amount of lubricant sprayed in each intestinal wall area and obtain the dosage requirement calculation result; in, is the lubricant injection amount, Indicates the lubricant quantity coefficient per unit friction force, is the real-time friction value of the intestinal wall area, is the base of natural logarithms, is the friction response coefficient, is the reference friction value; The lubricant application parameter calculation submodule adjusts the injection parameters of the lubricant based on the dosage requirement calculation result to generate a lubricant application parameter set.

[0013] Compared with the prior art, the advantages and positive effects of the present invention are: In the present invention, the intestinal wall distance is acquired in real time, the focal length parameters of the lens group are adjusted, the image clarity is optimized, the image changes are analyzed, the compression ratio of the image data is dynamically adjusted, the image data stream is optimized, the data transmission delay and bandwidth occupancy are reduced, and the image analysis is combined to identify the roughness of the intestinal wall surface and the morphological changes of the intestine, and the catheter advancement force parameters are dynamically adjusted to ensure the smoothness and safety of the catheter insertion. By calculating the injection amount of the lubricant at multiple positions, the application of the lubricant is accurately controlled, thereby improving the visualization effect of the enema operation, the operation accuracy and the patient comfort, and optimizing the diagnosis and treatment process. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] Figure 1 is a system flow chart of the present invention; Figure 2 This is a flow chart of the automatic focus adjustment module of the present invention; Figure 3 It is a flow chart of the data flow optimization module of the present invention; Figure 4 It is a flow chart of the roughness analysis module of the present invention; Figure 5 This is a flow chart of the propulsion trajectory calculation module of the present invention; Figure 6 This is a flow chart of the lubricant application module of the present invention. DETAILED DESCRIPTION

[0015] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0016] In the description of the present invention, it should be understood that the terms "length", "width", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside" and the like indicate positions or positional relationships based on the positions or positional relationships shown in the drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as limiting the present invention. In addition, in the description of the present invention, "multiple" means two or more, unless otherwise clearly and specifically defined.

[0017] See also Figure 1 , an enema auxiliary system with integrated lubrication and visual catheter includes: The focus automatic adjustment module calls the ultrasonic sensor to obtain the intestinal wall distance data in real time and calculates the intestinal wall distance change. By analyzing the relationship between the focus offset and the intestinal wall distance change, the focus parameter of the lens group is adjusted to obtain the focus adjustment parameter. The image data stream optimization module obtains the image frame sequence of the front end of the intestinal catheter in real time based on the focal length adjustment parameters, detects and calculates the pixel displacement and brightness change between adjacent frames, and adjusts the compression ratio of the image data according to the degree of change between adjacent frames to obtain the optimized image data stream; The roughness analysis module obtains the image frame sequence of the intestinal contact area based on the optimized image data stream, detects the brightness gradient change and pixel edge contour density of the contact area between the catheter and the intestinal wall, calculates the pixel density change rate of the contact area, analyzes the surface roughness gradient distribution of the contact area, and obtains the roughness distribution value; The propulsion trajectory calculation module calls the image data based on the roughness distribution value, identifies the morphological changes of the intestine, including contraction and expansion, calculates the changes of intestinal friction and propulsion resistance, adjusts the catheter propulsion force parameters, and obtains the propulsion force parameters; The intelligent lubricant application module calculates the injection amount of lubricant at multiple positions based on the propulsion force parameters and the real-time friction force of the catheter in multiple intestinal wall areas to obtain the lubricant application parameters.

[0018] The focal length adjustment parameters specifically include the focal length offset correction value, the lens group adjustment coefficient, and the intestinal wall distance change rate. The optimized image data stream includes the pixel displacement calculation results, the brightness change analysis results, and the data compression ratio adjustment value. The roughness distribution value specifically includes the contact area pixel density change rate, the friction gradient calculation value, and the intestinal contact pressure distribution data. The propulsion force parameters include the propulsion force adjustment coefficient, the intestinal friction calculation result, and the resistance change trend value. The lubricant application parameters specifically refer to the lubricant injection amount calculation value, the injection position distribution data, and the lubrication coverage range.

[0019] See also Figure 2 , the focus automatic adjustment module includes: The ultrasonic data acquisition submodule calls the ultrasonic sensor, monitors the distance between the intestinal wall and the sensor by analyzing the real-time output signal of the sensor, collects the time series data of the intestinal wall distance, and generates a real-time intestinal wall distance data set; In the ultrasonic data acquisition submodule, the real-time output signal of the ultrasonic sensor is first obtained to monitor the distance between the intestinal wall and the sensor. Specifically, through the ultrasonic sensor connected to the device, the sensor starts to emit ultrasonic signals at a certain frequency and receives its reflected signals. The distance between the sensor and the intestinal wall is determined by calculating the propagation time of the sound wave, and then the distance data between the intestinal wall and the sensor is obtained in real time. In practical applications, for example, an ultrasonic signal is sent to a certain intestinal segment through a handheld device. Assuming that the time required for the signal to be emitted to the intestinal wall and reflected back to the sensor is 2 microseconds, and assuming that the propagation speed of ultrasonic waves in the air is 343 meters / second, the roughness analysis module uses the formula: ; Calculate the distance between the intestinal wall and the sensor. Through such operations, the real-time distance data of the intestinal wall can be obtained and a set of data sets can be formed. Specifically, if the time for the sensor to measure the reflected signal at a certain moment is 2 microseconds, the distance calculation is: ; In this process, the threshold setting is used to distinguish normal changes from abnormal changes in the data. For example, suppose a standard threshold is set , which is used to determine whether there are significant abnormal fluctuations in the continuous measurement value changes. If the change in the distance between the intestinal wall and the sensor exceeds the threshold, the change is considered abnormal, and the data point is marked for further processing. The choice of threshold is set according to the accuracy of the equipment and the maximum error range measured during the experiment. Therefore, setting it to 0.005mm is reasonable and can effectively distinguish between small changes and large fluctuations. Finally, the ultrasonic data acquisition submodule generates and outputs the real-time intestinal wall distance dataset.

[0020] The distance change analysis submodule calculates the intestinal wall distance change between consecutive time points based on the intestinal wall real-time distance data set, analyzes the change trend, and obtains the intestinal wall distance change data; In the intestinal wall distance change analysis submodule, based on the intestinal wall real-time distance dataset, this module calculates the intestinal wall distance change between consecutive time points. Specifically, this module calculates the difference between each time point in the dataset, obtains the distance change, and analyzes the change trend. The formula used is: ; Calculate the distance change, where and are the intestinal wall distance data of continuous measurement points, Represents the change in distance between each pair of consecutive data points.

[0021] For example, suppose the data set contains the following consecutive measurements: 0.343mm, 0.345mm, 0.347mm, 0.350mm, and the changes in the intestinal wall distance are: ; ; ; Based on these changes, the module further screens out larger change intervals and analyzes their regularity and trends to obtain "intestinal wall distance change data."

[0022] During this process, a benchmark value was set to screen for significant changes. , when the change in intestinal wall distance is greater than the baseline value, the change is considered significant. Exceeding the set benchmark value of 0.0025mm indicates that the change is beyond the normal fluctuation range and is a significant change. This benchmark value is set based on the sensitivity of the device and the minimum change detection capability in actual applications to ensure that the roughness analysis module captures changes caused by abnormal intestinal wall movement or other factors. Finally, the intestinal wall distance change data is output.

[0023] The focal length parameter adjustment submodule calls the intestinal wall distance change data, analyzes the relationship between the focal length offset and the intestinal wall distance change, and adjusts the focal length parameters of the lens group by calculating the degree of offset, using the formula: ; Calculate the optimal value of focal length adjustment and generate focal length adjustment parameters; in, Represents the focal length adjustment value, and are the maximum and minimum values ​​of the intestinal wall distance, is the intestinal wall distance measured in a single time, is the average intestinal wall distance, is the current lens focal length parameter, is the focal length offset, Represents the index of a single data point in the intestinal wall distance measurement data, Represents the total number of measurements; In the focal parameter adjustment submodule, the intestinal wall distance change data is called to analyze the relationship between the focal offset and the intestinal wall distance change. Based on this data, the module calculates the necessity of focal adjustment and then adjusts the focal parameters of the lens group. For example, assuming that the maximum intestinal wall distance is 0.350mm, the minimum is 0.343mm, the focal offset is 0.05mm, and the current focal parameter of the lens group is 10mm. Substitute these data into the formula: ; Calculate the difference between the maximum and minimum values ​​of the intestinal wall distance: ; Calculate the standard deviation of the distance change: ; ; ; ; ; Compute the sum of the squares of the differences between each data point and the mean: ; Calculate the standard deviation: ; Calculate the focus adjustment value: ; In this process, the weight The setting is used to reflect the difficulty and range of adjusting the focal length of the current lens group, assuming it is 10mm. Represents the focal length adjustment, assuming it is 0.05mm, indicating the effect of the offset. Through this formula, the focal length adjustment amount is finally 0.0011mm, indicating that the focal length adjustment amount is very small, and the focal length of the lens group can be fine-tuned to obtain accurate imaging effects, generating a focal length adjustment parameter set.

[0024] See also Figure 3 , the data flow optimization module includes: The image frame sequence acquisition submodule obtains the image frame sequence of the front end of the intestinal catheter by receiving the continuous image data stream output by the camera in real time based on the focal length adjustment parameter, and generates an image frame data set; In the image frame sequence acquisition submodule, the image frame sequence of the front end of the intestinal catheter is first acquired through the image acquisition device. This process involves real-time reception and storage of continuous image data streams. The sensor quickly captures the corresponding image information according to the current operating environment and generates a series of data frames. To achieve this goal, the image sensor used by the device, such as CMOS or CCD sensor, will be cached in memory or directly transmitted to the computing processing unit for each frame to ensure that the image data can be streamed according to real-time requirements. For example, during real-time image capture, the device may acquire data at a rate of 30 frames per second, with a time interval of 1 / 30 second for each frame, that is, the time delay for each frame is 33 milliseconds. If the device is configured for 30 frames per second, each frame is kept in the system cache for 33 milliseconds. These image data are quickly sent to the subsequent processing link through the transmission interface. In actual applications, if the frame rate is set to 30 frames per second, the device will generate 30 image frame data per second to form an image frame data set.

[0025] The adjacent frame variation calculation submodule analyzes the pixel differences between each pair of adjacent frames based on the image frame data set, calculates the pixel displacement and brightness variation, obtains the inter-frame variation, and generates pixel displacement and brightness variation data; In the adjacent frame variation calculation submodule, the pixel displacement and brightness variation of each pair of adjacent frames in the image frame data set are calculated. The pixel difference between each pair of consecutive frames is first detected and their brightness values ​​are compared. Specifically, the pixel difference is calculated based on the pixel information in each frame. Assume that the first frame and the second frame of the image are and , pixel displacement is the difference in pixel position between the two frames, expressed by the following formula: ; in, and The images are and Middle The brightness value of a pixel, is the total number of pixels in the image. By calculating all pixel differences and accumulating them, we get the pixel displacement For example, between the first frame and the second frame, the calculated pixel difference is 150 pixels. Next, calculate the brightness change , this process is based on the brightness comparison of each pair of adjacent frames, and the brightness change is calculated by the following formula: ; in, and are the average brightness values ​​of the first frame and the second frame respectively. Assume and , then the brightness change is .

[0026] During the operation, the brightness value of each pixel is first extracted from each frame of the image and stored, and then these values ​​are compared one by one to calculate the brightness difference and pixel change between the two frames. This process may involve the support of image processing software or hardware accelerators to ensure real-time processing of each frame of data. In specific implementation, the device will calculate the changes between pixels in real time and perform brightness difference calculations through the image processing module. Assuming that the image contains 1000 pixels, the total displacement is obtained by accumulating the pixel difference values ​​one by one. If the difference is 150 pixel units during calculation, and the brightness change threshold is set to 3, only the frame pairs whose changes exceed the threshold are considered to have significant changes, and then need to be processed in the subsequent compression ratio adjustment. In this way, through detailed steps and calculations, the pixel displacement and brightness change data can be finally obtained, which can be used for further image optimization and adjustment in subsequent modules.

[0027] The data compression ratio adjustment submodule analyzes the degree of change between adjacent frames based on the pixel displacement and brightness change data, using the formula: ; Obtaining the optimized compression ratio value and generating an optimized image data stream; in, represents the compression ratio adjustment parameter, Represents the pixel displacement of each frame, Represents the size of the current frame, Represents the brightness change, represents the frame time interval, Represents the total number of frames in the image frame dataset, Represents the index of each frame of data; In the data compression ratio adjustment submodule, the degree of change between adjacent frames is evaluated based on the pixel displacement and brightness change data. If the pixel displacement and brightness change between adjacent frames are small, the compression ratio of the image data is reduced, otherwise the compression ratio is increased. Specifically, the specific value of the compression ratio is adjusted by weighting the pixel displacement and brightness change between each pair of adjacent frames. The setting formula is as follows: ; in, represents the compression ratio adjustment parameter, is the pixel displacement of each frame, is the size of the current frame, Represents the brightness change, Represents the time interval of each frame. Assume that in the calculation, the sum of pixel displacements , frame size , brightness change , time interval seconds (33 milliseconds), then after entering the formula: ; Therefore, the compression ratio adjustment parameter is 0.983, which indicates that the compression ratio of the data stream is relatively low and suitable for maintaining high image quality. Finally, the optimized image data stream is generated.

[0028] See also Figure 4 , the roughness analysis module includes: The image frame acquisition submodule extracts intestinal wall images at multiple time points by optimizing the image data stream and obtains the image frame sequence of the intestinal contact area; By optimizing the image data stream, the image frame sequence of the intestinal contact area is obtained, and the intestinal wall images at different time points are extracted to ensure the integrity and timeliness of the image data. The image acquisition device captures the image information of the contact between the intestine and the catheter in real time and generates an image frame sequence. In this process, the time interval of each frame image is calculated and the quality of the image data is analyzed. Assume that the acquired image frame sequence is ,in For the Frame image, is the acquisition time of the frame, then the time interval between image frames is expressed as: ; Among them, the table Shidi Frame and The time interval between frames. This time interval is used to evaluate the acquisition speed and continuity of image data.

[0029] Assume that the acquisition time of the first frame is 0.5 seconds, the acquisition time of the second frame is 1.0 seconds, and the acquisition time of the third frame is 1.5 seconds, then: Second; Second; In this way, the time interval between all image frames is 0.5 seconds, ensuring the continuity and timeliness of acquisition.

[0030] The brightness gradient analysis submodule detects the brightness gradient change of the contact area between the catheter and the intestinal wall based on the image frame sequence of the intestinal contact area, and analyzes the pixel edge contour density of the contact area to obtain the brightness gradient change; Based on the image frame sequence, the brightness gradient change of the contact area between the catheter and the intestinal wall is detected, and the pixel edge contour density of the contact area is analyzed. By detecting the brightness gradient change of each frame of the image, the change of the contact area between the intestinal wall and the catheter can be identified, and the brightness change rate can be further calculated to quantify the friction characteristics of the contact area.

[0031] Assume that the brightness information of the image is given by express, and is the pixel coordinate of the image, then the brightness gradient It can be obtained by calculating the brightness difference of adjacent pixels: ; in, and The image brightness is and Directional derivative. Calculated Represents the brightness change of each pixel in the image.

[0032] Assume that the brightness of adjacent pixels in a certain area is and , then the brightness gradient is calculated as: ; ; ; This value indicates that the brightness gradient between these two pixels is 20.

[0033] The roughness gradient calculation submodule compares the correlation between the brightness gradient and the pixel edge contour density according to the brightness gradient change, using the formula: ; Calculate the roughness of multiple locations and generate roughness distribution values; in, represents the friction value at position c, represents the brightness of the image at position c, represents the brightness gradient change at position c, represents the pixel density at position c, represents the edge contour density of the dth pixel at the cth position, represents the average edge contour density at position c, Represents the number of pixel edges at each location; According to the pixel density change rate of the contact area, the correlation between the brightness gradient and the pixel edge contour density is compared, and the friction value of each position is calculated point by point to generate the friction values ​​of multiple positions. By calculating the roughness gradient of each frame of the image, the roughness distribution map is finally obtained.

[0034] Based on the relationship between the change in brightness gradient and pixel density in the contact area, the friction force distribution value is calculated. Assume that at each position The brightness gradient change is , the pixel density is , friction value It is expressed as: ; in, represents the friction value at position c, For the The brightness of the position image, For the The brightness gradient change at the position, For the The pixel density of the location, For the Position The edge contour density of pixels, For the The average edge contour density at the location, is the number of pixel edges at each location.

[0035] Assume The brightness of the position is , the brightness gradient change is , the pixel density is , and the pixel edge density data at this location is ,but: ; ; ; ; ; Therefore, the location The friction value is 64.8.

[0036] See also Figure 5 , the propulsion trajectory calculation module includes: The real-time morphology recognition submodule calls the image data based on the roughness distribution value, identifies the contraction and expansion state of the intestine by calculating the contour changes in each frame of the image, marks the regional changes of contraction and expansion, and generates a data set of intestinal morphology changes; Based on the roughness distribution value, the image data is called, and the contraction and expansion states of the intestine are identified by calculating the contour changes in each frame of the image, marking the regional changes of contraction and expansion, and generating a data set of intestinal morphological changes. First, the contour information of each frame is extracted from the image data, and the boundary of the intestine is identified using an edge detection algorithm. Then, the contour displacement between adjacent frames is calculated. Areas with a displacement greater than 0.5 mm are marked as expanded, and areas with a displacement less than -0.5 mm are marked as contracted. For example, in a certain frame, if the contour displacement of a certain area is 0.6 mm, it is marked as expansion, and if the displacement is -0.7 mm, it is marked as contraction. Through frame-by-frame analysis, a data set of intestinal morphological changes containing all frames is generated. Calculation formula: ; in, Indicates the displacement in millimeters. represents the contour change, Indicates a time interval.

[0037] Assume that the contour change of a frame mm, time interval seconds, the displacement is: mm; According to the judgment criteria, the displacement is greater than 0.5 mm, so the area is marked as dilated.

[0038] The resistance calculation submodule calculates the friction and propulsion resistance changes of the intestine through the intestinal morphology change data set, combined with the brightness gradient and roughness distribution value of the contact area between the catheter and the intestinal wall, and generates friction and resistance data; Through the intestinal morphological change data set, combined with the brightness gradient and friction distribution of the contact area between the catheter and the intestinal wall, the friction and propulsion resistance changes of the intestine are calculated to generate friction and resistance data. First, the contour displacement data of each frame is extracted from the morphological change data set. Combined with the brightness gradient data, the area with a brightness gradient greater than 50 is marked as a high friction area, and the area with a brightness gradient less than 30 is marked as a low friction area. For example, if the brightness gradient of a certain area in a certain frame is 60, it is marked as a high friction area, and if the brightness gradient is 20, it is marked as a low friction area. Then, according to the friction distribution data, the friction value of each frame is calculated. The area with a friction value greater than 0.8 Newton is marked as a high resistance area, and the area with a friction value less than 0.3 Newton is marked as a low resistance area. For example, if the friction value of a certain area in a certain frame is 0.9 Newton, it is marked as a high resistance area, and if the friction value is 0.2 Newton, it is marked as a low resistance area. Through frame-by-frame analysis, friction and resistance data containing all frames are generated. Calculation formula: ; in, represents the friction force, represents the friction coefficient, Represents the brightness gradient.

[0039] Assume that the brightness gradient of a certain area , friction coefficient , then the friction force: ; According to the judgment criteria, the friction value is greater than 0.8 Newton, so the area is marked as a high resistance area.

[0040] The propulsion force adjustment submodule is based on the friction and resistance data through the formula: ; Calculate the propulsion force and obtain the propulsion force parameter; in, Represents the driving force, Represents the pixel displacement of each frame, represents the change in friction, represents the current resistance of the catheter, Represents the amount of resistance change to be adjusted, represents the adjusted intestinal friction, Represents the resistance adjustment value required when the catheter is advanced; Based on the friction and resistance data, the propulsion force is calculated by the formula to obtain the propulsion force parameters. First, the friction change value and resistance value of each frame are extracted from the friction and resistance data. For example, the friction change value of a certain frame is 0.5 Newtons, and the resistance value is 0.6 Newtons. Then, the propulsion force is calculated according to the formula. The pixel displacement in the formula is obtained through the contour displacement data. For example, the pixel displacement of a certain frame is 0.7 mm, and the adjusted resistance change is 0.2 Newtons. Substitute these values ​​into the formula to calculate the propulsion force value. For example, the propulsion force value of a certain frame is 1.2 Newtons. By calculating frame by frame, the propulsion force parameters of all frames are obtained.

[0041] Calculation formula: ; in, Indicates the strength of advancement. Represents the pixel displacement of each frame, represents the change in friction, represents the current resistance of the catheter, Indicates the amount of resistance change that is adjusted.

[0042] Assume that the pixel displacement of a frame mm, Friction change Newton, current resistance of the catheter Newton, the amount of resistance change to adjust Newton, the propulsion force: : The results showed that the propulsion force was 0.4375 Newtons, which was used to adjust the force when the catheter was pushed.

[0043] See also Figure 6 , the lubricant application module includes: The friction force analysis submodule further calculates the friction force data of the contact area between the catheter and the intestinal wall in the intestine based on the propulsion force parameter and the propulsion force of the catheter at multiple intestinal wall locations to obtain real-time friction force data; Based on the propulsion force parameter, the propulsion force of the catheter at multiple intestinal wall positions is measured and recorded. These data are collected in real time by sensors. The sensors convert the propulsion force into electrical signals and transmit them to the data processing unit. The data processing unit converts the electrical signals into friction force values ​​according to a preset algorithm. The friction force values ​​are calculated by comparing the propulsion force differences at different intestinal wall positions to obtain the friction data of the contact area between the catheter and the intestinal wall. For example, when the propulsion force of the catheter at a certain intestinal wall position is 0.5N, the friction force data is calculated to be 0.2N. These data are displayed in real time on the monitoring screen for the operator's reference. During the acquisition of real-time friction force data, the operator adjusts the propulsion speed and angle of the catheter according to the change in the friction force value to ensure the smooth propulsion of the catheter in the intestine. During the calculation of the friction force data, the data processing unit calls the preset friction force calculation formula, substitutes the propulsion force parameter into the formula, and calculates the friction force value. For example, when the propulsion force is 0.5N, the friction force calculation formula is: ; in, is the friction coefficient, To promote the strength, assume is 0.4, is 0.5, then: ; During the real-time update of friction data, the data processing unit updates the friction value every 0.1 seconds to ensure the real-time and accuracy of the data. The results of real-time friction data are stored in the database for subsequent analysis and use.

[0044] The lubricant demand assessment submodule uses the formula based on real-time friction data: ; Calculate the amount of lubricant sprayed in each intestinal wall area and obtain the dosage requirement calculation result; in, is the lubricant injection amount, Indicates the lubricant quantity coefficient per unit friction force, is the real-time friction value of the intestinal wall area, is the base of natural logarithms, is the friction response coefficient, is the reference friction value; According to the real-time friction data, the lubricant injection amount is calculated by the formula: ; Calculate, where is the lubricant quantity coefficient per unit friction, is the real-time friction value, is the base of natural logarithms, is the friction response coefficient, is the reference friction value, for example, when is 0.1, 0.2N, is 2, When it is 0.15N: ; During the calculation of the lubricant injection amount, the data processing unit calls a preset lubricant injection amount calculation formula, substitutes the real-time friction force value into the formula, calculates the lubricant injection amount, and the calculation result of the lubricant injection amount is transmitted to the lubricant injection control system. The control system adjusts the lubricant injection parameters according to the calculation results. For example, when the lubricant injection amount is 0.0095ml, the control system adjusts the injection time to 0.1 seconds and the injection pressure to 0.05MPa. During the real-time adjustment of the lubricant injection amount, the control system updates the injection parameters every 0.1 seconds to ensure that the lubricant injection amount matches the real-time friction force data. The calculation result of the lubricant injection amount is stored in the database for subsequent analysis and use.

[0045] The lubricant application parameter calculation submodule adjusts the injection parameters of the lubricant based on the dosage requirement calculation result to generate a lubricant application parameter set; Based on the dosage requirement calculation results, the lubricant injection parameters are achieved by adjusting the injection time and injection pressure. For example, when the lubricant injection amount is 0.0095 ml, the injection time is adjusted to 0.1 second and the injection pressure is adjusted to 0.05 MPa. During the adjustment of the lubricant injection parameters, the control system calls the preset injection parameter adjustment algorithm, substitutes the lubricant injection amount into the algorithm, calculates the injection time and injection pressure, and the adjustment results of the lubricant injection parameters are transmitted to the lubricant injection device, which injects lubricant according to the adjusted parameters. For example, when the injection time is 0.1 second and the injection pressure is 0.05 MPa, the device injects 0.0095 ml of lubricant at a pressure of 0.05 MPa within 0.1 second. During the real-time adjustment of the lubricant injection parameters, the control system updates the injection parameters every 0.1 second to ensure that the lubricant injection amount matches the real-time friction data. The adjustment results of the lubricant injection parameters are stored in the database for subsequent analysis and use.

[0046] Table 1: Lubricant injection parameter adjustment table ; As shown in Table 1, the lubricant injection parameters are adjusted according to the lubricant injection amount. The setting values ​​of injection time and injection pressure are calculated through actual examples to ensure that the lubricant injection amount matches the real-time friction data.

[0047] The above are only preferred embodiments of the present invention and are not intended to limit the present invention in other forms. Any technician familiar with the profession may use the technical contents disclosed above to change or modify them into equivalent embodiments with equivalent changes and apply them to other fields. However, any simple modification, equivalent change and modification made to the above embodiments based on the technical essence of the present invention without departing from the technical solution of the present invention still falls within the protection scope of the technical solution of the present invention.

Claims

1. An enema auxiliary system with integrated lubrication and visual catheter, characterized in that: The system comprises: The focus automatic adjustment module calls the ultrasonic sensor to obtain the intestinal wall distance data in real time and calculates the intestinal wall distance change. By analyzing the relationship between the focus offset and the intestinal wall distance change, the focus parameter of the lens group is adjusted to obtain the focus adjustment parameter. The data stream optimization module acquires the image frame sequence of the front end of the intestinal catheter in real time based on the focal length adjustment parameter, calculates the pixel displacement and brightness change between adjacent frames, evaluates the degree of change, adjusts the compression ratio of the image data, and obtains an optimized image data stream; The roughness analysis module analyzes the image frame sequence based on the optimized image data stream, calculates the pixel density change rate of the intestinal contact area, analyzes the surface roughness gradient distribution of the contact area, and obtains the roughness distribution value; The propulsion trajectory calculation module calls the image data based on the roughness distribution value, identifies the morphological changes of the intestine, calculates the changes of the intestinal friction and propulsion resistance, adjusts the catheter propulsion force parameters, and obtains the propulsion force parameters.

2. The enema auxiliary system with integrated lubrication and visual catheter according to claim 1, characterized in that: The focal length adjustment parameters specifically include the focal length offset correction value, the lens group adjustment coefficient, and the intestinal wall distance change rate; the optimized image data stream includes the pixel displacement calculation results, the brightness change analysis results, and the data compression ratio adjustment value; the roughness distribution value specifically includes the contact area pixel density change rate, the friction gradient calculation value, and the intestinal contact pressure distribution data; the propulsion force parameters include the propulsion force adjustment coefficient, the intestinal friction calculation result, and the resistance change trend value.

3. The enema auxiliary system with integrated lubrication and visual catheter according to claim 1, characterized in that: The system further comprises: The lubricant application module calculates the injection amount of the lubricant at multiple locations based on the propulsion force parameter and the real-time friction force of the catheter on multiple intestinal wall areas to obtain the lubricant application parameter; The lubricant application parameters specifically refer to the lubricant injection amount calculation value, injection position distribution data, and lubrication coverage.

4. The enema auxiliary system with integrated lubrication and visual catheter according to claim 1, characterized in that: The focus automatic adjustment module comprises: The ultrasonic data acquisition submodule calls the ultrasonic sensor, monitors the distance between the intestinal wall and the sensor by analyzing the real-time output signal of the sensor, collects the time series data of the intestinal wall distance, and generates a real-time intestinal wall distance data set; The distance change analysis submodule calculates the intestinal wall distance change between consecutive time points based on the intestinal wall real-time distance data set, analyzes the change trend, and obtains intestinal wall distance change data; The focal length parameter adjustment submodule calls the intestinal wall distance change data, analyzes the relationship between the focal length offset and the intestinal wall distance change, and adjusts the focal length parameters of the lens group by calculating the degree of offset, using the formula: ； Calculate the optimal value of focal length adjustment and generate focal length adjustment parameters; in, Represents the focal length adjustment value, and are the maximum and minimum values ​​of the intestinal wall distance, is the intestinal wall distance measured in a single time, is the average intestinal wall distance, is the current lens focal length parameter, is the focal length offset, Represents the index of a single data point in the intestinal wall distance measurement data, Represents the total number of measurements.

5. The enema auxiliary system with integrated lubrication and visual catheter according to claim 1, characterized in that: The data flow optimization module includes: The image frame sequence acquisition submodule acquires the image frame sequence of the front end of the catheter in the intestine based on the focal length adjustment parameter by receiving the continuous image data stream output by the camera in real time, and generates an image frame data set; The adjacent frame variation calculation submodule analyzes the pixel difference between each pair of adjacent frames based on the image frame data set, calculates the pixel displacement and brightness variation, obtains the inter-frame variation, and generates pixel displacement and brightness variation data; The data compression ratio adjustment submodule analyzes the degree of change between adjacent frames according to the pixel displacement and brightness change data, using the formula: ； Obtaining the optimized compression ratio value and generating an optimized image data stream; in, represents the compression ratio adjustment parameter, Represents the pixel displacement of each frame, Represents the size of the current frame, Represents the brightness change, represents the frame time interval, Represents the total number of frames in the image frame dataset, Represents the index of each frame of data.

6. The enema auxiliary system with integrated lubrication and visual catheter according to claim 1, characterized in that: The roughness analysis module includes: The image frame acquisition submodule extracts intestinal wall images at multiple time points through the optimized image data stream to obtain an image frame sequence of the intestinal contact area; The brightness gradient analysis submodule detects the brightness gradient change amount of the contact area between the catheter and the intestinal wall based on the image frame sequence of the intestinal contact area, and analyzes the pixel edge contour density of the contact area to obtain the brightness gradient change amount; The roughness gradient calculation submodule compares the correlation between the brightness gradient and the pixel edge contour density according to the brightness gradient change, and adopts the formula: ； Calculate the roughness of multiple locations and generate roughness distribution values; in, represents the friction value at position c, represents the brightness of the image at position c, represents the brightness gradient change at position c, represents the pixel density at position c, represents the edge contour density of the dth pixel at the cth position, represents the average edge contour density at position c, Represents the number of pixel edges at each location.

7. The enema auxiliary system with integrated lubrication and visual catheter according to claim 1, characterized in that: The propulsion trajectory calculation module includes: The real-time morphology recognition submodule calls the image data based on the roughness distribution value, identifies the contraction and expansion state of the intestine by calculating the contour changes in each frame of the image, marks the regional changes of contraction and expansion, and generates an intestinal morphology change data set; The resistance calculation submodule calculates the intestinal friction and propulsion resistance changes through the intestinal morphology change data set, combined with the brightness gradient and roughness distribution value of the contact area between the catheter and the intestinal wall, and generates friction and resistance data; The propulsion force adjustment submodule is based on the friction and resistance data, through the formula: ； Calculate the propulsion force and obtain the propulsion force parameter; in, Represents the driving force, Represents the pixel displacement of each frame, represents the change in friction, represents the current resistance of the catheter, Represents the amount of resistance change to be adjusted, represents the adjusted intestinal friction, Represents the resistance adjustment value required when advancing the catheter.

8. The enema auxiliary system with integrated lubrication and visualization catheter according to claim 3, characterized in that: The lubricant application module comprises: The friction force analysis submodule further calculates the friction force data of the contact area between the catheter and the intestinal wall in the intestine based on the propulsion force parameter and the propulsion force of the catheter at multiple intestinal wall positions to obtain real-time friction force data; The lubricant demand assessment submodule uses the formula based on the real-time friction data: ； Calculate the amount of lubricant sprayed in each intestinal wall area and obtain the dosage requirement calculation result; in, is the lubricant injection amount, Indicates the lubricant quantity coefficient per unit friction force, is the real-time friction value of the intestinal wall area, is the base of natural logarithms, is the friction response coefficient, is the reference friction value; The lubricant application parameter calculation submodule adjusts the injection parameters of the lubricant based on the dosage requirement calculation result to generate a lubricant application parameter set.

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