Intelligent negative pressure drainage system for pancreatic anastomosis in pancreatic fistula monitoring

Abstract

The present application relates to the technical field of medical equipment, and more particularly to a pancreatic anastomosis intelligent negative pressure drainage system for pancreatic fistula monitoring, which comprises: a baseline construction module for constructing an individual reference baseline data set within a preset time period; an enzyme concentration detection module for detecting whether the pancreatic amylase concentration in the drainage fluid exceeds an abnormal trigger threshold; a tube state identification module for determining a tube state identification result through tube state visual identification and flow rate consistency verification when the enzyme concentration abnormal duration exceeds a threshold; a saturation compensation module for extracting the plateau of the pancreatic amylase concentration curve and judging whether the saturation sequence of each detection point meets the requirements; and a correction module for correcting the initial negative pressure when the saturation sequence requirements are not met. Through the cooperation of multiple modules, the present application realizes real-time and accurate monitoring of the pancreatic anastomosis fistula, improves the reliability and response speed of postoperative complication identification, and provides intelligent drainage state judgment and early warning support for clinical use.

Description

Technical Field

[0001] This invention relates to the field of medical device technology, and in particular to an intelligent negative pressure drainage system for pancreatic anastomosis for monitoring pancreatic fistula. Background Technology

[0002] Current pancreatic fistula monitoring techniques mainly rely on postoperative drainage fluid pancreatic enzyme concentration analysis or manual visual inspection of the drainage tube status. However, traditional methods have significant limitations.

[0003] First, in existing technologies, pancreatic enzyme concentration detection typically relies on traditional colorimetric or spectrophotometric methods. These methods are not only cumbersome and time-consuming, but also lack the ability to resist interference from the complex matrix of drainage fluid, especially common components such as hemoglobin, which can easily interfere with the test results. Furthermore, existing testing equipment largely depends on large laboratory instruments, making it impossible to achieve bedside real-time testing and automated analysis, thus failing to meet the clinical needs of real-time postoperative monitoring.

[0004] Secondly, single-point pancreatic enzyme concentration or manual visual judgment is easily affected by instantaneous fluctuations, sampling errors and subjective factors, resulting in inaccurate judgment of the degree of pancreatic juice leakage.

[0005] Furthermore, existing negative pressure drainage systems are mostly designed with fixed parameters, lacking the ability to dynamically adjust based on changes in fluid flow or pancreatic enzyme concentration within the tube, thus reducing drainage efficiency and the timeliness of complication warnings. Finally, traditional techniques do not adequately utilize tube status information, failing to combine flow rate changes with changes in drainage tube morphology, making it difficult to effectively identify abnormalities affecting pancreatic enzyme flow, such as bends and fluid column breakage.

[0006] Therefore, existing technologies have limitations in terms of real-time performance, accuracy, and dynamic control capabilities, making it difficult to provide reliable and intelligent monitoring and early warning support for pancreatic fistulas in clinical practice.

[0007] Chinese Patent Publication No. CN120037471A discloses a water-pumping and mixing type postoperative drainage device for pancreatic cancer, including a negative pressure pump chamber. The negative pressure pump chamber is provided with an inlet and an outlet. The inlet is connected to a water inlet pipe and a first drainage pipe, and the outlet is connected to a second drainage pipe. The end of the water inlet pipe is connected to a water supply tank, and the end of the second drainage pipe is connected to a storage tank. A first flow chamber and a second flow chamber are formed inside the negative pressure pump chamber. A first pipe chamber and a second pipe chamber are connected between the first flow chamber and the second flow chamber. A one-way valve structure is provided at the connection between the first flow chamber, the second flow chamber and the first pipe chamber, the second pipe chamber.

[0008] It is evident that existing medical device technologies mainly rely on postoperative drainage fluid pancreatic enzyme concentration testing or manual visual inspection of the drainage tube status, which makes it difficult to reflect changes in the drainage fluid in real time and lacks the ability to dynamically adjust based on changes in the fluid flow or pancreatic enzyme concentration within the tube. Summary of the Invention

[0009] Therefore, the present invention provides an intelligent negative pressure drainage system for pancreatic anastomosis for monitoring pancreatic fistula. This system overcomes the problem in the prior art where the detection of drainage fluid components is delayed, leading to the inability to automatically adjust negative pressure or trigger an alarm, through the coordinated determination of a continuous triggering mechanism for pancreatic enzyme abnormalities and the verification of visual flow velocity in the tube, as well as the dynamic correction of negative pressure.

[0010] To achieve the above objectives, the present invention provides an intelligent negative pressure drainage system for pancreatic anastomosis for monitoring pancreatic fistula, comprising:

[0011] The baseline construction module is used to collect various characteristic data of the drainage fluid under initial negative pressure on the negative pressure drainage path placed at the drainage point within a preset baseline data collection time period, and to construct an individual reference baseline dataset based on the aforementioned characteristic data.

[0012] The enzyme concentration detection module is connected to the baseline construction module. It is used to collect the characteristic data within a preset offset detection time period to determine whether the pancreatic amylase concentration in the drainage fluid is greater than the enzyme abnormality trigger threshold.

[0013] The tube state recognition module is connected to the enzyme concentration detection module. It is used to obtain the tube state recognition result after tube state visual recognition and flow rate consistency verification when the pancreatic amylase concentration is greater than the enzyme abnormality trigger threshold and the corresponding pancreatic amylase concentration abnormality duration is greater than the preset enzyme abnormality duration threshold.

[0014] The saturation compensation module, connected to the tube state recognition module, is used to update the detection points with plateau phase in the pancreatic amylase concentration curve as the detection points when the first tube state recognition result is obtained. Based on the time difference of any one of the detection points entering the plateau phase, it is determined whether the saturation state of each detection point meets the saturation order requirements.

[0015] The correction module is connected to the baseline construction module and the saturation compensation module respectively, and is used to adjust the initial negative pressure when the saturation sequence requirements are not met.

[0016] Furthermore, the enzyme concentration detection module includes an enzyme concentration detection unit, a duration recognition unit, and an enzyme concentration change rate calculation result generation unit;

[0017] The enzyme concentration detection unit is used to obtain the instantaneous detection concentration value of pancreatic amylase in the drainage fluid at several detection points in the negative pressure drainage path.

[0018] The duration recognition unit is connected to the enzyme concentration detection unit and is used to record the duration of enzyme abnormality at any detection point when the instantaneous detection concentration value of pancreatic enzyme at any detection point is greater than the preset enzyme abnormality trigger threshold.

[0019] The enzyme concentration change rate calculation result generation unit is connected to the duration identification unit to calculate the concentration change rate, compare the enzyme abnormal duration with a preset enzyme abnormal duration threshold, and generate a pancreatic amylase concentration abnormality determination result when the enzyme abnormal duration is greater than the enzyme abnormal duration threshold.

[0020] Furthermore, the pipe state recognition module includes a flow rate detection unit, a lighting unit, a pipe state visual recognition unit, and a flow rate consistency verification unit;

[0021] A flow rate detection unit is used to construct a flow rate change sequence based on the instantaneous detected concentration values;

[0022] The lighting unit is connected to the flow rate detection unit and is used to apply a uniform lighting source close to the outside of the drainage tube;

[0023] The tube state visual recognition unit is connected to the flow velocity detection unit to identify the appearance shape and continuous state of the tube wall contour under uniform illumination, and generate the initial tube state judgment result corresponding to each detection point.

[0024] The flow velocity consistency verification unit is connected to the flow velocity detection unit and the pipe state visual recognition unit, respectively, and is used to obtain the pipe state recognition result based on the initial pipe state determination result and the flow velocity change sequence.

[0025] Furthermore, the tube-shaped visual recognition unit includes an appearance shape recognition subunit, a bend angle judgment subunit, and a tube internal liquid column distribution recognition subunit;

[0026] The appearance and shape recognition subunit is used to obtain the surface brightness of the drainage tube under the uniform illumination source and extract the continuous line segment of the tube wall contour at this time.

[0027] The angle judgment subunit is connected to the appearance shape recognition subunit and is used to determine whether there is an angle state based on the continuous line segment of the pipe wall outline and the brightness of the drainage tube surface.

[0028] The in-tube liquid column distribution identification subunit is connected to the angle judgment subunit to identify the continuous state of the in-tube liquid column distribution and generate the corresponding in-tube liquid column distribution judgment result.

[0029] Furthermore, the flow rate consistency verification unit includes an ideal velocity estimation unit and a velocity comparison subunit;

[0030] An ideal velocity estimation unit is used to estimate the ideal flow velocity at each detection point by combining the initial pipe state determination results at each detection point;

[0031] The velocity comparison subunit is used to obtain the actual flow velocity at each detection point in the flow velocity change sequence, and to determine the pipe state identification result corresponding to the flow velocity difference between the actual flow velocity and the ideal flow velocity at each detection point.

[0032] Furthermore, the saturation compensation module includes a distance acquisition unit and a plateau period extraction unit;

[0033] A distance acquisition unit is used to acquire the label corresponding to each detection point and the fixed interval between each adjacent detection point;

[0034] The plateau phase extraction unit, connected to the distance acquisition unit, is used to extract the plateau phase from the detection curve of pancreatic amylase concentration changing with time at each detection point after the pancreatic amylase concentration is greater than the enzyme abnormality trigger threshold and the corresponding enzyme abnormality duration meets the preset duration threshold.

[0035] Furthermore, the saturation compensation module also includes a saturation state determination unit;

[0036] The saturation state judgment unit is connected to the distance acquisition unit and the detection point extraction subunit, respectively. It is used to update and obtain a number of detection points, and determine whether the saturation state of each detection point meets the saturation order requirements based on the time difference between any randomly selected detection point entering the plateau period.

[0037] Furthermore, the saturation state determination unit includes a detection point extraction subunit and a saturation order determination subunit;

[0038] The detection point extraction sub-unit is used to obtain detection points that have plateau periods and update them as points to be detected.

[0039] The saturation order judgment subunit is connected to the detection point extraction subunit. It is used to select one detection point from a number of detection points, obtain the timestamps of the two detection points entering the plateau period, calculate the time difference, and judge whether the saturation state of each detection point meets the saturation order requirements based on the comparison result of the time difference and the preset saturation order judgment threshold.

[0040] Furthermore, the correction module includes a first correction unit and a second correction unit;

[0041] The first correction unit is used to adjust the initial negative pressure with a first negative pressure adjustment step size when a broken liquid column exists in the entire detection range.

[0042] The second correction unit, connected to the first correction unit, is used to adjust the initial negative pressure with a second negative pressure adjustment step size when the saturation sequence requirement is not met.

[0043] Furthermore, the second correction unit includes a second step size calculation subunit and a correction subunit;

[0044] The second step size calculation subunit is used to calculate the second negative pressure adjustment step size based on the time difference;

[0045] The correction subunit is connected to the second step size calculation subunit and is used to adjust the initial negative pressure according to the second negative pressure adjustment step size.

[0046] Compared with existing technologies, the advantages of this invention lie in the fact that by introducing a continuous and stable negative pressure regulation mechanism into the pancreatic anastomosis drainage path, the drainage fluid can be continuously discharged under low resistance, thereby maintaining the dynamic balance of the fluid environment around the anastomosis. The negative pressure level is adjusted according to the actual drainage status, avoiding drainage retention caused by insufficient negative pressure and tissue traction or local ischemia caused by excessive negative pressure. This ensures that the anastomosis area is always in a controllable and stable mechanical environment, which helps reduce the risk of pancreatic juice accumulation in the local area. At the same time, in response to the needs of pancreatic fistula monitoring, key parameters of the drainage fluid are continuously acquired and analyzed, enabling abnormal changes to be detected before the appearance of clinical symptoms. This invention improves the sensitivity and stability of abnormality identification by comprehensively judging the composition and state of drainage fluid, reducing accidental misjudgments caused by single-point detection, and making the monitoring results closer to the actual state of the anastomosis, thus providing reliable data support for postoperative management. Ultimately, it establishes a closed-loop correlation between the monitoring results and negative pressure drainage control, matching the drainage intensity with the actual risk state and achieving integrated coordination of drainage and monitoring. This invention reduces the reliance on frequent manual intervention while alleviating the workload of medical staff, and provides a clear and executable technical path for continuous observation and risk control of postoperative pancreatic anastomosis, contributing to improved stability and predictability of overall management.

[0047] Furthermore, by continuously and dynamically monitoring the concentration of pancreatic amylase at multiple detection points in the negative pressure drainage pathway, and combining the concentration threshold, duration threshold, and rate of change triple judgment mechanism, the influence of instantaneous fluctuations and occasional interference on the judgment results can be effectively suppressed, improving the stability and accuracy of pancreatic amylase abnormality identification, which is conducive to improving the consistency and reliability of pancreatic fistula monitoring results.

[0048] Furthermore, by constructing a flow rate change sequence and combining it with tube-state visual recognition under uniform illumination, continuous monitoring of the flow rate and morphology of the drainage tube can be achieved. This can accurately determine whether there are abnormal bends or flow rate deviations in the drainage tube, ensuring the reliability of pancreatic enzyme concentration monitoring and drainage effect. Attached Figure Description

[0049] Figure 1 This is a connection diagram of the intelligent negative pressure drainage system for pancreatic anastomosis used for monitoring pancreatic fistula according to an embodiment of the present invention;

[0050] Figure 2 This is a connection diagram of the tube state recognition module according to an embodiment of the present invention;

[0051] Figure 3 This is a logic decision diagram of the saturation time calculation unit in an embodiment of the present invention;

[0052] Figure 4 This is a connection diagram of the correction module in an embodiment of the present invention. Detailed Implementation

[0053] To make the objectives and advantages of the present invention clearer, the present invention will be further described below with reference to embodiments; it should be understood that the specific embodiments described herein are merely for explaining the present invention and are not intended to limit the present invention.

[0054] Preferred embodiments of the present invention will now be described with reference to the accompanying drawings. Those skilled in the art should understand that these embodiments are merely illustrative of the technical principles of the present invention and are not intended to limit the scope of protection of the present invention.

[0055] It should be noted that in the description of this invention, the terms "upper", "lower", "left", "right", "inner", "outer", etc., which indicate directions or positional relationships, are based on the directions or positional relationships shown in the accompanying drawings. This is only for the convenience of description and is not intended to indicate or imply that the device or element must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, it should not be construed as a limitation of this invention.

[0056] Furthermore, it should be noted that, in the description of this invention, unless otherwise explicitly specified and limited, the terms "installation," "connection," and "linking" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection of two components. Those skilled in the art can understand the specific meaning of the above terms in this invention according to the specific circumstances.

[0057] Please see Figure 1 The diagram shown is a connection schematic of an intelligent negative pressure drainage system for pancreatic anastomosis used for monitoring pancreatic fistula according to an embodiment of the present invention. The present invention provides an intelligent negative pressure drainage system for pancreatic anastomosis used for monitoring pancreatic fistula, comprising:

[0058] The baseline construction module is used to collect various characteristic data of the drainage fluid under initial negative pressure on the negative pressure drainage path placed at the drainage point within a preset baseline data collection time period, and to construct an individual reference baseline dataset based on the aforementioned characteristic data.

[0059] The enzyme concentration detection module is connected to the baseline construction module. It is used to collect the characteristic data within a preset offset detection time period to determine whether the pancreatic amylase concentration in the drainage fluid is greater than the enzyme abnormality trigger threshold.

[0060] The tube state recognition module is connected to the enzyme concentration detection module. It is used to obtain the tube state recognition result after tube state visual recognition and flow rate consistency verification when the pancreatic amylase concentration is greater than the enzyme abnormality trigger threshold and the corresponding pancreatic amylase concentration abnormality duration is greater than the preset enzyme abnormality duration threshold.

[0061] The saturation compensation module, connected to the tube state recognition module, is used to update the detection points with plateau phase in the pancreatic amylase concentration curve as the detection points when the first tube state recognition result is obtained. Based on the time difference of any one of the detection points entering the plateau phase, it is determined whether the saturation state of each detection point meets the saturation order requirements.

[0062] The correction module is connected to the baseline construction module and the saturation compensation module respectively, and is used to adjust the initial negative pressure when the saturation sequence requirements are not met.

[0063] In this embodiment, pancreatic amylase concentration refers to the pancreatic amylase content detected in the negative pressure drainage fluid, which reflects the degree of pancreatic fluid leakage; enzyme abnormality trigger threshold refers to a preset concentration limit value used to determine whether the pancreatic amylase concentration changes from a normal state to an abnormal state; abnormal duration refers to the continuous length of time that the pancreatic amylase concentration remains above the enzyme abnormality trigger threshold; enzyme abnormality duration threshold refers to the minimum duration used to determine whether the enzyme concentration abnormality is persistent; tube state visual recognition refers to the process of identifying the appearance and bend features of the drainage tube through image analysis under uniform lighting conditions; flow rate consistency verification refers to comparing the detected changes in the flow rate of the drainage fluid with the tube state visual recognition results to verify the consistency of the two in physical state.

[0064] Tube state identification result refers to the conclusion of the current structural state of the drainage tube obtained by combining visual tube state identification and flow rate consistency verification; first tube state identification result refers to the tube state identification result obtained by re-identifying the drainage tube state after the duration of enzyme abnormality meets the threshold condition; plateau period refers to the time segment in the curve of pancreatic amylase concentration changing with time from a fluctuating state to a relatively stable level; time difference refers to the difference between the timestamps of pancreatic amylase concentration entering the plateau period corresponding to different detection points.

[0065] The saturation sequence requirement refers to the criterion used to determine whether the order in which each detection point enters the plateau phase conforms to the point-to-point propagation law along the negative pressure drainage direction.

[0066] In this embodiment, the drainage point is the location where the negative pressure drainage path is placed and comes into contact with the human skin;

[0067] The detection zone extends distally from the pancreatic anastomosis along the axial direction of the negative pressure drainage path. Several detection points are set within the detection zone, with each detection point arranged sequentially along the axial direction of the drainage tube. Each detection point is equipped with an independent light source to provide localized and uniform illumination to the corresponding tube segment. The spacing between adjacent detection points can be set to a fixed distance or can be set unequally according to the length of the drainage tube, monitoring accuracy requirements, and clinical deployment conditions to meet the needs of acquiring and aligning detection signals at different detection points.

[0068] By introducing a continuous and stable negative pressure regulation mechanism into the pancreatic anastomosis drainage pathway, the drainage fluid can be continuously discharged under low resistance, thereby maintaining the dynamic balance of the fluid environment around the anastomosis. The negative pressure level is adjusted according to the actual drainage status to avoid drainage retention caused by insufficient negative pressure, and tissue traction or local ischemia caused by excessive negative pressure. This ensures that the anastomosis area is always in a controllable and stable mechanical environment, which helps reduce the risk of pancreatic juice accumulation in the local area. At the same time, to meet the monitoring needs of pancreatic fistula, key parameters of the drainage fluid are continuously acquired and analyzed, so that abnormal changes can be identified in time before clinical symptoms appear. Through the analysis of the drainage fluid... The comprehensive assessment of composition and drainage status enhances the sensitivity and stability of abnormality identification, reduces accidental misjudgments caused by single-point-of-life detection, and makes monitoring results closer to the actual state of the anastomosis, providing reliable data support for postoperative management. Ultimately, the monitoring results are linked to negative pressure drainage control in a closed loop, matching the drainage intensity with the actual risk status and achieving integrated coordination of drainage and monitoring. This invention reduces the reliance on frequent manual intervention while alleviating the workload of medical staff. At the same time, it provides a clear and executable technical path for continuous observation and risk control of the postoperative pancreatic anastomosis, which helps to improve the stability and predictability of overall management.

[0069] Specifically, the enzyme concentration detection module includes an enzyme concentration detection unit, a duration recognition unit, and an enzyme concentration detection result generation unit;

[0070] The enzyme concentration detection unit is used to obtain the instantaneous concentration of pancreatic amylase in the drainage fluid at several detection points in the negative pressure drainage path, employing a highly specific reaction system based on the colorimetric principle. Specifically, 2-chloro-4-nitrophenylmaltotriose glycoside (CNP-G3) is selected as the specific substrate for pancreatic amylase. Under the catalysis of pancreatic amylase, CNP-G3 hydrolyzes to generate the intermediate product 2-chloro-4-nitrophenol, which, through a built-in enzyme-coupled long-wavelength signal transduction system, ultimately generates a stable dye with strong characteristic absorption in the wavelength range of 570-600 nm. This wavelength range effectively avoids the absorption peaks of common interfering substances such as hemoglobin in the drainage fluid, thereby significantly improving the specificity and anti-interference ability of the detection. All reaction reagents (including CNP-G3 substrate, buffer salt, signal transduction enzyme, and chromogenic precursor) are pre-prepared into lyophilized reagent balls with precise proportions and encapsulated in a micro-reaction chamber. After the drainage sample flows in, the reagent is automatically reconstituted and the reaction is initiated, achieving an extremely simple "one-step sample addition" operation. The reaction chamber integrates a miniature optical path, consisting of a specific wavelength (570-600 nm) LED light source and a narrow-band filter. The transmitted light signal is received and converted into an electrical signal by a high-gain, low-noise, and high-frame-rate linear array vision chip. The chip's high gain (>10) 5 The A / W ratio, wide dynamic range (>120 dB), and high frame rate (1000 Hz) ensure accurate capture of subtle color change signals in complex drainage fluid samples and strong anti-interference capabilities. The analog signal output by the vision chip is initially conditioned by the transimpedance amplification and filtering circuit integrated within the module to form a stable analog voltage or digital signal. This signal characterizes the real-time concentration and changes of pancreatic amylase at the detection point and is transmitted to the upper-level unit as the "instantaneous detection concentration value" required by the system.

[0071] The duration recognition unit is connected to the enzyme concentration detection unit and is used to record the duration of enzyme abnormality at any detection point when the instantaneous detection concentration value of pancreatic enzyme at any detection point is greater than the preset enzyme abnormality trigger threshold.

[0072] An enzyme concentration detection result generation unit, connected to the duration recognition unit, is used to compare the abnormal enzyme duration with a preset abnormal enzyme duration threshold, and generate an abnormal pancreatic amylase concentration determination result when the abnormal enzyme duration is greater than the abnormal enzyme duration threshold.

[0073] In this embodiment, the instantaneous detection concentration value refers to the pancreatic amylase concentration data obtained at each detection point at the current acquisition time;

[0074] Specifically, the instantaneous detection concentration values ​​of pancreatic amylase obtained at each detection point are compared with the preset enzyme abnormality trigger threshold.

[0075] When the instantaneous concentration of pancreatic amylase at any detection point exceeds the enzyme abnormality trigger threshold, the detection point is determined to be in an enzyme abnormality state, and the duration of the abnormality at the detection point is recorded.

[0076] The duration of the enzyme abnormality is the duration during which the instantaneous detection concentration of pancreatic amylase at the detection point remains continuously greater than the enzyme abnormality trigger threshold.

[0077] When the duration of the enzyme abnormality exceeds a preset enzyme abnormality duration threshold, an abnormality determination result for the pancreatic amylase concentration at the corresponding detection point is generated. In this embodiment, the enzyme abnormality triggering threshold is an empirically set parameter, with a value range of 300 U / L to 3000 U / L, preferably 1000 U / L; the enzyme abnormality duration threshold is an empirically set parameter, with a value range of 10 min to 120 min, preferably 30 min.

[0078] When the instantaneous concentration of pancreatic amylase at all detection points is less than or equal to the enzyme abnormal trigger threshold, it is determined that the current pancreatic amylase concentration in the drainage fluid is in a normal state, and the system maintains the initial negative pressure drainage condition.

[0079] The instantaneous detection concentration values ​​of pancreatic amylase are all derived from real-time detection data collected at each detection point.

[0080] By continuously monitoring pancreatic amylase concentration at multiple detection points in the negative pressure drainage pathway, and combining a dual judgment mechanism of concentration threshold and duration threshold, the influence of transient fluctuations and occasional interference on the judgment results can be effectively suppressed, improving the stability and accuracy of pancreatic amylase abnormality identification, which is conducive to improving the consistency and reliability of pancreatic fistula monitoring results.

[0081] See Figure 2 The diagram shown is a connection schematic of the tube state recognition module according to an embodiment of the present invention.

[0082] Specifically, the pipe state recognition module includes a flow rate detection unit, a lighting unit, a pipe state visual recognition unit, and a flow rate consistency verification unit;

[0083] A flow rate detection unit is used to construct a flow rate change sequence based on the instantaneous detected concentration values;

[0084] The lighting unit is connected to the flow rate detection unit and is used to apply a uniform lighting source close to the outside of the drainage tube;

[0085] The tube state visual recognition unit is connected to the flow velocity detection unit and is used to identify the appearance shape and continuous state of the tube wall outline of the drainage tube under uniform illumination, and generate the initial tube state judgment result corresponding to each detection point.

[0086] The flow velocity consistency verification unit is connected to the flow velocity detection unit and the pipe state visual recognition unit, respectively, and is used to obtain the pipe state recognition result based on the initial pipe state determination result and the flow velocity change sequence.

[0087] In this embodiment, the flow rate change sequence refers to a time series formed by orderly recording the continuous data of the flow rate of the drainage fluid changing with time within the time interval for each detection point, with the end time of the preset baseline data acquisition period as the start time and the current real-time acquisition time as the end time. This time series is used to characterize the dynamic change characteristics of the flow rate at the corresponding detection point.

[0088] Applying uniform illumination close to the outside of the drainage tube means setting up independent light sources at the corresponding positions on the outer wall of the drainage tube at each detection point. The light sources are arranged close to the drainage tube along the axial or circumferential direction, so that the surface of the drainage tube forms stable illumination conditions without obvious light-dark gradients within the detection range.

[0089] By constructing a flow rate change sequence and combining it with tube state visual recognition under uniform illumination, continuous monitoring of the flow rate and morphology of the drainage tube can be achieved. This can accurately determine whether there are abnormal bends or flow rate deviations in the drainage tube, ensuring the reliability of pancreatic enzyme concentration monitoring and drainage effect.

[0090] Specifically, the tube-shaped visual recognition unit includes an appearance shape recognition subunit, a bend angle judgment subunit, and a tube internal liquid column distribution recognition subunit;

[0091] The appearance and shape recognition subunit is used to obtain the surface brightness of the drainage tube under the uniform illumination source and extract the continuous line segment of the tube wall contour at this time.

[0092] The angle judgment subunit is connected to the appearance shape recognition subunit and is used to determine whether there is an angle state based on the continuous line segment of the pipe wall outline and the brightness of the drainage tube surface.

[0093] The in-tube liquid column distribution identification subunit is connected to the angle judgment subunit to identify the continuous state of the in-tube liquid column distribution and generate the corresponding in-tube liquid column distribution judgment result.

[0094] In this embodiment, the surface of the drainage tube is illuminated by a uniform lighting source, so that the tube wall forms a stable brightness distribution within the detection range;

[0095] Based on the brightness image, extract continuous line segments of the pipe wall contour, that is, the center position line of the pipe wall along the cross-sectional direction of the drainage pipe;

[0096] The formula for calculating the angle determination threshold R is as follows:

[0097] R=k×D

[0098] Where D is the diameter of the drainage tube;

[0099] k is an empirically set proportionality coefficient, with a value ranging from 0.1 to 0.5, preferably 0.25;

[0100] Visual recognition yields the minimum radius within the contour arc.

[0101] The minimum radius and the angle determination threshold are compared;

[0102] If the minimum radius is greater than the bend detection threshold, it is determined to be a bend-free state, and a result indicating that the bend does not exist is generated. The continuous state of the liquid column distribution in the drainage tube is then identified.

[0103] Extract the shadow area of ​​the liquid column inside the drainage tube, and continuously scan the brightness change at each detection point along the tube axis. That is, identify the liquid column area by extracting the brightness features of the liquid inside the drainage tube in the image, and determine whether there is a broken liquid column.

[0104] If present, further determine whether the fractured liquid column is located within the entire detection range from the pipe opening to the last detection point;

[0105] Wherein, the tube opening refers to the inlet position of the drainage tube at the pancreatic anastomosis, and the last detection point refers to the last detection point set at the end of the drainage tube;

[0106] If a broken liquid column exists within the entire detection range, adjust the initial negative pressure;

[0107] If a broken liquid column exists within the entire detection range, perform the ideal velocity estimation step;

[0108] If the minimum radius is less than or equal to the corner determination threshold, it is determined to be a corner state, a corner existence result is generated, and a pipe state abnormality alarm is triggered.

[0109] By extracting continuous line segments of the tube wall contour and comparing them with an empirical threshold based on the minimum radius of the contour arc, the system can accurately identify the folding state, promptly determine whether the drainage tube has a fold and trigger abnormal processing, improve the accuracy and reliability of negative pressure drainage detection, and prevent the folding of the drainage tube from affecting the flow of drainage fluid and the detection results of pancreatic enzyme concentration.

[0110] By extracting continuous line segments of the tube wall contour and identifying the shadowed area of ​​the liquid column inside the tube, accurate judgment of bends and liquid column breaks can be achieved, timely triggering of abnormal alarms, improving the accuracy and reliability of drainage tube monitoring, ensuring that the pancreatic enzyme concentration detection results truly reflect the state of the drainage fluid, and preventing bends or broken liquid columns from affecting the flow rate and data analysis.

[0111] Specifically, the flow rate consistency verification unit includes an ideal velocity estimation unit and a velocity comparison subunit;

[0112] An ideal velocity estimation unit is used to estimate the ideal flow velocity at each detection point by combining the initial pipe state determination results at each detection point;

[0113] The velocity comparison subunit is used to obtain the actual flow velocity at each detection point in the flow velocity change sequence, and to determine the pipe state identification result corresponding to the flow velocity difference between the actual flow velocity and the ideal flow velocity at each detection point.

[0114] In this embodiment, the average flow rate V of the drainage fluid obtained at each detection point within the preset baseline data acquisition time period is used as the basis for the calculation. baseline As a reference value for ideal flow velocity;

[0115] The specific formula is as follows:

[0116] V ideal =V baseline ×(1+α)

[0117] Among them, V ideal The ideal flow rate at each detection point;

[0118] V baseline This represents the average flow velocity at the corresponding detection point within the baseline time period;

[0119] α is an empirical correction coefficient, ranging from -0.05 to 0.05, which can be finely adjusted according to the patient's postoperative condition. In this embodiment, it is taken as -0.03.

[0120] Obtain the current real-time flow velocity V at each detection point actual Calculate the velocity difference between the actual flow velocity and the ideal flow velocity:

[0121] ΔV=|V actual -V ideal |

[0122] The flow rate difference is compared with a preset flow rate difference threshold, which is an empirical parameter based on the baseline flow rate change amplitude, and the value range is 0.05 to 0.2 mL / s, preferably 0.1 mL / s;

[0123] If the flow velocity difference is greater than the preset flow velocity difference threshold, the flow velocity at the detection point is determined to be abnormal, and the first tube state identification result is obtained.

[0124] If the flow rate difference is less than or equal to the preset flow rate difference threshold, the flow rate at the detection point is determined to be normal, and the second tube state identification result is obtained.

[0125] By comparing the real-time detected flow rate with the ideal value, the risk of misjudgment based on a single threshold can be reduced, enabling accurate and adaptive identification of the functional status of the drainage tube.

[0126] Specifically, the saturation compensation module includes a distance acquisition unit and a plateau period extraction unit;

[0127] A distance acquisition unit is used to acquire the label corresponding to each detection point and the fixed interval between each adjacent detection point;

[0128] The plateau phase extraction unit, connected to the distance acquisition unit, is used to extract the plateau phase from the detection curve of pancreatic amylase concentration changing with time at each detection point after the pancreatic amylase concentration is greater than the enzyme abnormality trigger threshold and the corresponding enzyme abnormality duration meets the preset duration threshold.

[0129] In this embodiment, the distance acquisition unit acquires the label corresponding to each detection point, from the first detection point, the second detection point, and so on to the last detection point, with each detection point numbered in a fixed order.

[0130] Simultaneously, the fixed interval distance between adjacent detection points is obtained, which can be preset according to the layout of the drainage tube and the installation position of the sensor;

[0131] For the detection curve of pancreatic amylase concentration changing over time at each detection point, the plateau period is extracted. The plateau period is the time when the change in pancreatic amylase concentration is less than the set fluctuation threshold, that is, when the sensor reading tends to saturate or remain constant.

[0132] The fluctuation threshold is set as an empirical parameter, generally ranging from 5 U / L to 50 U / L, with 10 U / L being preferred. When the change in pancreatic amylase concentration at a certain detection point is less than or equal to the set fluctuation threshold during the continuous collection period, it is determined that the detection point is in a plateau period at the corresponding time and thereafter.

[0133] By extracting the plateau phase from the pancreatic amylase concentration curves at each detection point, the system can effectively identify whether the sensor is saturated or the concentration remains constant, thus eliminating misjudgments caused by signal fluctuations.

[0134] Specifically, the saturation compensation module further includes a saturation state determination unit;

[0135] The saturation state judgment unit is connected to the distance acquisition unit and the detection point extraction subunit, respectively, and is used to update and obtain a number of detection points. Based on the time difference of any randomly selected detection point entering the plateau period, it judges whether the saturation state of each detection point meets the saturation order requirements.

[0136] By sequentially determining the time difference between each detection point entering the plateau phase, dynamic monitoring and sequence verification of pancreatic amylase concentration saturation can be achieved. This enables timely detection of abnormal saturation sequences, ensuring the consistency and reliability of monitoring data, and providing an accurate basis for assessing the status of negative pressure drainage tubes.

[0137] See Figure 3 As shown, it is the logic decision diagram of the saturation time calculation unit in an embodiment of the present invention;

[0138] Specifically, the saturation state determination unit includes a detection point extraction subunit and a saturation order determination subunit;

[0139] The detection point extraction sub-unit is used to obtain detection points that have plateau periods and update them as points to be detected.

[0140] The saturation order judgment subunit is connected to the detection point extraction subunit. It is used to select one detection point from a number of detection points, obtain the timestamps of the two detection points entering the plateau period, calculate the time difference, and judge whether the saturation state of each detection point meets the saturation order requirements based on the comparison result of the time difference and the preset saturation order judgment threshold.

[0141] In this embodiment, the detection point extraction subunit obtains the detection points that have a plateau period, including all detection points from the first detection point, the second detection point, and the last detection point in sequence, and updates them to the set of detection points;

[0142] The saturation order judgment subunit can randomly select any one of the points to be detected in the set, obtain the timestamps of the two points entering the plateau period and calculate the time difference between the two timestamps;

[0143] The time difference is compared with a preset saturation order judgment threshold;

[0144] If the time difference is less than or equal to the preset saturation order judgment threshold, the saturation order of the pair of detection points is determined to meet the saturation order requirements, a saturation order result is generated, and the process of selecting one detection point and judgment steps is repeated for other detection points.

[0145] If the time difference is greater than the preset saturation order judgment threshold, the saturation order of the pair of detection points is determined to be inconsistent with the saturation order requirements, and a result indicating inconsistent saturation order is generated.

[0146] See Figure 4 As shown, it is a connection diagram of the correction module in an embodiment of the present invention;

[0147] Specifically, the correction module includes a first correction unit and a second correction unit;

[0148] The first correction unit is used to adjust the initial negative pressure with a first negative pressure adjustment step size when a broken liquid column exists in the entire detection range.

[0149] The second correction unit, connected to the first correction unit, is used to adjust the initial negative pressure with a second negative pressure adjustment step size when the saturation sequence requirement is not met.

[0150] In this embodiment, when a broken liquid column exists in the entire detection range, the first correction unit increases the initial negative pressure by a preset first negative pressure adjustment step size.

[0151] The first negative pressure adjustment step is an empirical parameter that can be set according to the diameter of the drainage tube and the condition of the liquid column breakage. The general range is 0.1 to 0.5 kPa, preferably 0.25 kPa.

[0152] After the adjustment, the system re-executed the pancreatic amylase concentration acquisition and subsequent steps.

[0153] The initial negative pressure is adjusted by the first correction unit according to the preset step size to realize automatic compensation of the broken liquid column, ensure the continuity of the liquid column in the drainage tube, maintain the stability of pancreatic amylase concentration collection, and improve the accuracy and reliability of tube monitoring.

[0154] Specifically, the second correction unit includes a second step size calculation subunit and a correction subunit;

[0155] The second step size calculation subunit is used to calculate the second negative pressure adjustment step size based on the time difference;

[0156] The correction subunit is connected to the second step size calculation subunit and is used to adjust the initial negative pressure according to the second negative pressure adjustment step size.

[0157] In this embodiment, the second negative pressure adjustment step size is obtained by calculating the difference between the time difference of each detection point entering the plateau period and the preset saturation sequence judgment threshold, combined with the empirical correction coefficient W.

[0158] The formula for calculating the second negative pressure adjustment step size is as follows:

[0159] Second negative pressure adjustment step size = W × (time difference - preset saturation order judgment threshold) / preset saturation order judgment threshold

[0160] Wherein, W is an empirical correction coefficient, which can be set according to the diameter of the drainage tube and the condition of the liquid column breakage. Generally, the value ranges from 0.1 to 0.5, with 0.25 being preferred.

[0161] The correction subunit adjusts the initial negative pressure according to the second negative pressure adjustment step size. At the same time, it adjusts the second negative pressure adjustment step size in the same unit as the initial negative pressure to ensure that the saturation sequence of the drainage tube meets the requirements, and then re-collects and monitors the enzyme concentration.

[0162] By calculating the negative pressure adjustment step size based on the time difference of each detection point entering the plateau period and the preset threshold, the initial negative pressure is dynamically corrected. Combined with the empirical correction coefficient, the adjustment range is quantified to ensure that the saturation sequence of each detection point meets the requirements, optimize the continuity of the liquid column and the stability of the tube, improve the accuracy and reliability of pancreatic amylase concentration collection and monitoring, and prevent the impact of liquid column breakage or abnormal sensor saturation sequence on drainage assessment.

[0163] The technical solution of the present invention has been described above with reference to the preferred embodiments shown in the accompanying drawings. However, it will be readily understood by those skilled in the art that the scope of protection of the present invention is obviously not limited to these specific embodiments. Without departing from the principles of the present invention, those skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the technical solutions after these changes or substitutions will all fall within the scope of protection of the present invention.

[0164] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. An intelligent negative pressure drainage system for pancreatic anastomosis for monitoring pancreatic fistula, characterized in that, include: The baseline construction module is used to collect various characteristic data of the drainage fluid under initial negative pressure on the negative pressure drainage path placed at the drainage point within a preset baseline data collection time period, and to construct an individual reference baseline dataset based on the aforementioned characteristic data. The enzyme concentration detection module is connected to the baseline construction module. It is used to collect the characteristic data within a preset offset detection time period to determine whether the pancreatic amylase concentration in the drainage fluid is greater than the enzyme abnormality trigger threshold. The tube state recognition module is connected to the enzyme concentration detection module. It is used to obtain the tube state recognition result after tube state visual recognition and flow rate consistency verification when the pancreatic amylase concentration is greater than the enzyme abnormality trigger threshold and the corresponding pancreatic amylase concentration abnormality duration is greater than the preset enzyme abnormality duration threshold. The saturation compensation module, connected to the tube state recognition module, is used to update the detection points with plateau phase in the pancreatic amylase concentration curve as the detection points when the first tube state recognition result is obtained. Based on the time difference of any one of the detection points entering the plateau phase, it is determined whether the saturation state of each detection point meets the saturation order requirements. The correction module is connected to the baseline construction module and the saturation compensation module respectively, and is used to adjust the initial negative pressure when the saturation sequence requirements are not met.

2. The intelligent negative pressure drainage system for pancreatic anastomosis for monitoring pancreatic fistula according to claim 1, characterized in that, The enzyme concentration detection module includes an enzyme concentration detection unit, a duration recognition unit, and an enzyme concentration change rate calculation unit. The enzyme concentration detection unit is used to obtain the instantaneous detection concentration value of pancreatic amylase in the drainage fluid at several detection points in the negative pressure drainage path. The duration recognition unit is connected to the enzyme concentration detection unit and is used to record the duration of enzyme abnormality at any detection point when the instantaneous detection concentration value of pancreatic enzyme at any detection point is greater than the preset enzyme abnormality trigger threshold. The enzyme concentration change rate calculation unit is connected to the duration identification unit. It is used to compare the abnormal enzyme duration with a preset abnormal enzyme duration threshold, and when the abnormal enzyme duration is greater than the abnormal enzyme duration threshold, calculate the enzyme concentration change rate over a period of time and generate an abnormal pancreatic amylase concentration determination result.

3. The intelligent negative pressure drainage system for pancreatic anastomosis for monitoring pancreatic fistula according to claim 2, characterized in that, The pipe state recognition module includes a flow velocity detection unit, a lighting unit, a pipe state visual recognition unit, and a flow velocity consistency verification unit; A flow rate detection unit is used to construct a flow rate change sequence based on the instantaneous detected concentration values; The lighting unit is connected to the flow rate detection unit and is used to apply a uniform lighting source close to the outside of the drainage tube; The tube state visual recognition unit is connected to the flow velocity detection unit to identify the appearance shape and continuous state of the tube wall contour under uniform illumination, and generate the initial tube state judgment result corresponding to each detection point. The flow velocity consistency verification unit is connected to the flow velocity detection unit and the pipe state visual recognition unit, respectively, and is used to obtain the pipe state recognition result based on the initial pipe state determination result and the flow velocity change sequence.

4. The intelligent negative pressure drainage system for pancreatic anastomosis for monitoring pancreatic fistula according to claim 3, characterized in that, The tube-state visual recognition unit includes an appearance shape recognition subunit, a bend angle judgment subunit, and a tube internal liquid column distribution recognition subunit; The appearance and shape recognition subunit is used to obtain the surface brightness of the drainage tube under the uniform illumination source and extract the continuous line segment of the tube wall contour at this time. The angle judgment subunit is connected to the appearance shape recognition subunit and is used to determine whether there is an angle state based on the continuous line segment of the pipe wall outline and the brightness of the drainage tube surface. The in-tube liquid column distribution identification subunit is connected to the angle judgment subunit to identify the continuous state of the in-tube liquid column distribution and generate the corresponding in-tube liquid column distribution judgment result.

5. The intelligent negative pressure drainage system for pancreatic anastomosis for monitoring pancreatic fistula according to claim 4, characterized in that, The flow velocity consistency verification unit includes an ideal velocity estimation unit and a velocity comparison subunit; An ideal velocity estimation unit is used to estimate the ideal flow velocity at each detection point by combining the initial pipe state determination results at each detection point; The velocity comparison subunit is used to obtain the actual flow velocity at each detection point in the flow velocity change sequence, and to determine the pipe state identification result corresponding to the flow velocity difference between the actual flow velocity and the ideal flow velocity at each detection point.

6. The intelligent negative pressure drainage system for pancreatic anastomosis for monitoring pancreatic fistula according to claim 1, characterized in that, The saturation compensation module includes a distance acquisition unit and a plateau period extraction unit; A distance acquisition unit is used to acquire the label corresponding to each detection point and the fixed interval between each adjacent detection point; The plateau phase extraction unit, connected to the distance acquisition unit, is used to extract the plateau phase from the detection curve of pancreatic amylase concentration changing with time at each detection point after the pancreatic amylase concentration is greater than the enzyme abnormality trigger threshold and the corresponding enzyme abnormality duration meets the preset duration threshold.

7. The intelligent negative pressure drainage system for pancreatic anastomosis for monitoring pancreatic fistula according to claim 6, characterized in that, The saturation compensation module also includes a saturation state judgment unit; The saturation state judgment unit is connected to the distance acquisition unit and the detection point extraction subunit, respectively, and is used to update and obtain a number of detection points. Based on the time difference of any randomly selected detection point entering the plateau period, it judges whether the saturation state of each detection point meets the saturation order requirements.

8. The intelligent negative pressure drainage system for pancreatic anastomosis for monitoring pancreatic fistula according to claim 7, characterized in that, The saturation state determination unit includes a detection point extraction subunit and a saturation order determination subunit; The detection point extraction sub-unit is used to obtain detection points that have plateau periods and update them as points to be detected. The saturation order judgment subunit is connected to the detection point extraction subunit. It is used to select one detection point from a number of detection points, obtain the timestamps of the two detection points entering the plateau period, calculate the time difference, and judge whether the saturation state of each detection point meets the saturation order requirements based on the comparison result of the time difference and the preset saturation order judgment threshold.

9. The intelligent negative pressure drainage system for pancreatic anastomosis for monitoring pancreatic fistula according to claim 1, characterized in that, The correction module includes a first correction unit and a second correction unit; The first correction unit is used to adjust the initial negative pressure with a first negative pressure adjustment step size when a broken liquid column exists in the entire detection range. The second correction unit, connected to the first correction unit, is used to adjust the initial negative pressure with a second negative pressure adjustment step size when the saturation sequence requirement is not met.

10. The intelligent negative pressure drainage system for pancreatic anastomosis for monitoring pancreatic fistula according to claim 9, characterized in that, The second correction unit includes a second step size calculation subunit and a correction subunit; The second step size calculation subunit is used to calculate the second negative pressure adjustment step size based on the time difference; The correction subunit is connected to the second step size calculation subunit and is used to adjust the initial negative pressure according to the second negative pressure adjustment step size.

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