Multi-bag independent control and intelligent circulation system of peritoneal dialysis equipment

Abstract

The present application relates to the technical field of peritoneal dialysis, in particular to a multi-bag independent control and intelligent circulation system of peritoneal dialysis equipment. The present application determines the correction residual amount based on the basic backflow residual amount and the basic perfusion residual amount adjusted by the flushing effect of the backflow of waste liquid, and the weight change of each drug liquid bag before and after dialysis circulation and the theoretical ultrafiltration amount. The characteristic correction residual amount is determined based on the state parameter difference of each drug liquid bag dialysis cycle and several dialysis cycles before it. The target flushing amount after each drug liquid bag dialysis cycle is determined based on the characteristic correction residual amount and the concentration gradient difference of the adjacent two circulation drug liquids, and the next drug liquid bag output target flushing amount is controlled to flush the pipeline with the drug liquid, and the generated flushing waste liquid is guided to the previous drug liquid bag to start the next drug liquid bag dialysis cycle. The present application realizes dynamic and accurate quantification of pipeline residual, combines physical correction and personalized habit calibration, and improves the pipeline flushing effect.

Description

Technical Field

[0001] This invention relates to the field of peritoneal dialysis technology, specifically to a multi-bag independent control and intelligent circulation system for peritoneal dialysis equipment. Background Technology

[0002] Peritoneal dialysis is an important renal replacement therapy for end-stage renal disease and is widely used for home treatment. Although automated peritoneal dialysis equipment has reduced the operational burden to some extent, there are still technical bottlenecks in switching control and residual management during the sequential perfusion of multiple bags of medication.

[0003] Current standard procedures employ a "fixed-volume flushing" strategy, where the tubing is flushed with a preset volume of fresh medication between two medication bags. However, in actual treatment, the residual volume in the tubing includes dead space in the multi-way valve, dead space at the bottom of the heating bag, and the total mass of fluid not completely returned after being adsorbed by the tubing. This volume falls within the effective resolution range of industrial weighing sensors and is affected by various dynamic factors such as medication viscosity, flow rate, temperature, tubing length, and individual patient differences (e.g., body position affecting return speed). Specifically, in high-viscosity environments (e.g., high-concentration glucose) or low-temperature environments, the residual layer on the tubing wall is thicker, and a fixed flushing volume may not be able to completely replace the residual fluid, leading to mixing of effective components and affecting treatment efficacy. In low-viscosity or high-speed perfusion conditions, the residual volume is smaller, and blindly using large-volume flushing will result in expensive waste of dialysate, increasing treatment costs. Summary of the Invention

[0004] To address the technical problem that a fixed-volume flushing strategy cannot dynamically adapt to changes in drug viscosity, flow rate, temperature, etc., resulting in inconsistent tubing residue and poor flushing effectiveness, this invention aims to provide a multi-bag independent control and intelligent circulation system for peritoneal dialysis equipment. The specific technical solution adopted is as follows: This invention proposes a multi-bag independent control and intelligent circulation system for a peritoneal dialysis device. The peritoneal dialysis device includes several drug solution bags connected by multi-channel tubing and a patient-end interface. The system includes: The data acquisition module is used to acquire different types of status parameters of the patient in each dialysis cycle of the drug bag compared with the previous several dialysis cycles; The residual analysis module is used to determine the basic perfusion residual amount and basic return residual amount of each dialysis cycle based on the structural parameters of the pipeline and the characteristic parameters of the drug solution in each drug solution bag and the waste liquid returned through the peritoneal cavity. The residual correction module is used to determine the corrected residual amount for each dialysis cycle of the drug bag based on the basic reflux residual amount and the scouring effect of the waste liquid reflux, as well as the weight change and theoretical ultrafiltration amount before and after each dialysis cycle of the drug bag. The feature calibration module is used to adjust the correction residue based on the difference in state parameters between each dialysis cycle of the drug bag and several previous dialysis cycles, and to determine the feature correction residue for each dialysis cycle of the drug bag. The flushing control module is used to determine the target flushing volume after each dialysis cycle of each drug bag based on the residual amount corrected by the characteristics and the concentration gradient difference between two adjacent cycles of drug solution, and to control the next drug bag to output the target flushing volume of drug solution to flush the pipeline, and to guide the generated flushing waste liquid to the previous drug bag to start the next dialysis cycle of the drug bag.

[0005] Further, determining the baseline perfusion residual volume and baseline reflux residual volume for each dialysis cycle of the drug bag includes: The inner surface area of ​​the tube, the adsorption coefficient of the tube, the thickness of the liquid film, and the density of the liquid in each medicine bag and the density of the waste liquid returned through the abdominal cavity were obtained. The density of the medicine in each medicine bag and the density of the waste liquid returned through the abdominal cavity are recorded as the analytical density. The product of the inner surface area of ​​each drug bag, the analytical density, and the liquid film thickness is taken as the liquid film residue. The product of the inner surface area of ​​each medicine bag and the adsorption coefficient of the tube is taken as the adsorption residue. The sum of the liquid film residue and the adsorption residue is used as the basic residue for each dialysis cycle of the drug bag; The baseline residual amounts corresponding to the medication in each medication bag and the waste fluid returned through the peritoneal cavity are sequentially used as the baseline perfusion residual amount and baseline return residual amount for each medication bag dialysis cycle. Further, the method for obtaining the theoretical ultrafiltration capacity includes: The formula for calculating the theoretical ultrafiltration capacity of each dialysis cycle using a drug bag is: In the formula, The theoretical ultrafiltration capacity for each dialysis cycle of the drug bag; The perfusion volume for each dialysis cycle of the drug bag; Density of the liquid in each medicine bag; Waste liquid density for each dialysis cycle of each drug bag; It is a preset minimum positive number.

[0006] Further, determining the corrected residual amount for each dialysis cycle of the drug bag includes: The scouring residual coefficient is determined by the waste liquid reflux rate of each dialysis cycle of the drug bag; the product of the basic perfusion residual amount and the scouring residual coefficient is calculated as the theoretical perfusion residual amount of each dialysis cycle of the drug bag. The sum of the theoretical perfusion residue for each dialysis cycle of the drug bag and the basic reflux residue is taken as the theoretical total residue. Obtain the increment of the drug bag after each dialysis cycle; take the difference between the theoretical ultrafiltration volume and the increment of the drug bag for each dialysis cycle as the actual residual amount; The corrected residual amount for each dialysis cycle of the drug solution bag is obtained by weighted summation of the theoretical total residual amount and the actual residual amount.

[0007] Further, determining the characteristic corrected residual amount for each dialysis cycle of the drug bag includes: Calculate the arithmetic mean of the same type of state parameters for several dialysis cycles prior to each drug bag dialysis cycle, and use it as the baseline state value for each type; Calculate the parameter difference between each type of state parameter and the baseline state value for each dialysis cycle of the drug bag; obtain the weight of each type of state parameter using a pre-built grey relational model; Calculate the product of the parameter difference value of each type of state parameter for each drug bag dialysis cycle and the weight, and sum the products corresponding to all types of state parameters as the state difference degree of the corresponding drug bag dialysis cycle; The corrected residual amount is weighted using the state difference degree to obtain the characteristic corrected residual amount for each dialysis cycle of the drug bag.

[0008] Further, the calculation of the parameter difference between each type of state parameter and the baseline state value for each dialysis cycle of the drug bag includes: All types of state parameters include continuous parameters and discrete parameters; For continuous parameters, the absolute difference between each type of state parameter and the reference state value is used as the numerator, and the ratio of the range of the corresponding type of state parameter to a preset minimum positive number is used as the denominator, which is the parameter difference value. For discrete parameters, when the absolute difference between each type of state parameter and the baseline state value is 0, the parameter difference value is set to 0; When the absolute difference between each type of state parameter and the baseline state value is within a preset range, the parameter difference value is set to the preset value. When the absolute difference between the state parameter value of each type and the baseline state value exceeds a preset range, the parameter difference value is set to 1.

[0009] Further, determining the target flush volume after each dialysis cycle of the drug bag includes: The difference between the waste liquid density of each dialysis cycle and the liquid density of the next dialysis bag is selected as the maximum value between zero and the maximum value. The sum of the product of the maximum value and the preset concentration risk gain factor and the preset baseline flushing ratio is used as the concentration gradient coefficient. The product of the characteristic correction residue of each drug bag dialysis cycle and the concentration gradient coefficient is used as the target flushing volume after each drug bag dialysis cycle.

[0010] Furthermore, the preset concentration risk gain factor is 5.

[0011] Further, the weighting of the corrected residual amount using the state difference degree includes: Calculate the sum of the product of the state difference degree and the preset fine-tuning coefficient for each dialysis cycle of the drug bag and the constant 1. Multiply the sum by the corrected residual amount as the characteristic corrected residual amount.

[0012] Furthermore, the method for obtaining the perfusion volume for each dialysis cycle of the drug bag includes: Obtain the weight of each medicine bag at the start of medicine infusion and the weight of each medicine bag at the end of medicine infusion; The ratio of the difference between the weight of the dialysis bag before and after the infusion begins to the density of the dialysis bag is used as the infusion volume for each dialysis cycle.

[0013] The present invention has the following beneficial effects: In this embodiment of the invention, based on pipeline structure parameters and fluid characteristic parameters, the perfusion residue (basic perfusion residue) and waste fluid return residue (basic return residue) are analyzed, providing a scientific basis for subsequent adaptive flushing and overcoming the limitations of traditional strategies that rely on experience-based preset flushing capacities. The residue correction module dynamically corrects the basic perfusion residue through the flushing effect of waste fluid return, accurately reflecting the flushing effect of waste fluid on the pipeline. Furthermore, it performs closed-loop calibration using the weight change of the drug bag before and after dialysis cycles and the theoretical ultrafiltration volume, effectively eliminating the cumulative errors caused by instantaneous fluctuations in temperature and flow rate in a single fluid model, making the corrected residue highly approximate the actual physical retention state of the pipeline. The feature calibration module, by longitudinally comparing the patient's historical dialysis cycle state parameters, keenly captures subtle shifts in the patient's individualized implicit fluid characteristics and dynamically adjusts the corrected residue, enabling the feature-corrected residue to automatically optimize as the patient's treatment habits evolve, solving the problem of inaccurate theoretical residue caused by operational differences. The target flushing volume is determined by combining the osmotic pressure risk and characteristic correction residue reflected by the concentration gradient of the two adjacent bags of medicine to avoid waste and cross-contamination of medicine; the mixed waste liquid generated by flushing is directed back into the medicine bag that has been emptied in the previous cycle, realizing "one bag for two purposes" - it can hold the original prescription medicine and also accommodate the flushing waste liquid of the corresponding cycle. Attached Figure Description

[0014] To more clearly illustrate the technical solutions and advantages in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0015] Figure 1 This is a system structure diagram of a multi-bag independent control and intelligent circulation system for a peritoneal dialysis device provided in one embodiment of the present invention; Figure 2 This is a schematic diagram of a computer device for a multi-bag independent control and intelligent circulation device of a peritoneal dialysis apparatus provided in one embodiment of the present invention. Detailed Implementation

[0016] To further illustrate the technical means and effects adopted by the present invention to achieve its intended purpose, the following, in conjunction with the accompanying drawings and preferred embodiments, details the specific implementation, structure, features, and effects of a multi-bag independent control and intelligent circulation system for peritoneal dialysis equipment proposed according to the present invention. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. Furthermore, specific features, structures, or characteristics in one or more embodiments can be combined in any suitable form.

[0017] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains.

[0018] One embodiment of the present invention provides a peritoneal dialysis device, comprising several drug solution bags, a heating bag, a multi-channel valve assembly, a bidirectional reversible pump assembly, and a patient-end interface connected by multi-channel tubing. Furthermore, the system integrates a sensor network, including a weighing sensor for real-time monitoring of drug solution weight changes and a temperature sensor for monitoring fluid temperature. The multi-channel valve assembly is used to switch the flow paths between different drug solution bags, heating bags, and the patient-end interface, and the pump assembly is used to drive the drug solution flow (infusion, refluxing, flushing). All components are connected to a central control unit to achieve fully automated closed-loop control of the dialysis process.

[0019] For any given medicine bag, denoted as the i-th bag, its complete dialysis cycle control logic is as follows: (1) The central control unit sends a command to switch the multi-way valve assembly to the state where the i-th bag and the heating bag are connected. The pump group starts and draws the preset amount of dialysate from the i-th bag and delivers it to the heating bag; then, the temperature control module of the heating bag starts and heats the dialysate to a suitable temperature for the human body and maintains a constant temperature. (2) After heating is completed, the multi-way valve is switched again to connect the pipeline to the interface between the heating bag and the patient end, and the warm dialysate is injected into the patient's peritoneal cavity through the pipeline by gravity or the pump group. (3) When all the dialysate is injected, the pump group is stopped and the relevant valves are closed, and the patient enters the pre-set retention stage; during this period, the dialysate exchanges substances with the blood through the peritoneum and undergoes ultrafiltration dehydration in the peritoneal cavity. (4) After the retention is completed, the control unit switches the multi-way valve to the state where the patient end interface and the i-th bag are connected; the pump group is started to run in reverse to return all the dialysis waste and ultrafiltration water in the peritoneal cavity to the i-th bag, realizing the "two uses of one bag" of the drug bag and the closed-loop recycling of waste liquid. (5) When the waste liquid is returned, the main process of the i-th bag ends. At this time, the system starts the flushing control model and calculates the target flushing volume after the i-th bag dialysis cycle is completed based on the residual amount in the pipeline. The control unit switches the multi-way valve to briefly connect the next drug bag (i+1 bag, which is ready to enter the next drug bag according to the preset prescription) with the i-th bag, and uses the drug liquid of i+1 bag to perform quantitative flushing of the pipeline, and accurately guides the generated flushing waste liquid to the i-th bag. (6) After confirming that the pipeline is clean, the i+1 bag dialysis cycle process is executed (repeating steps 1-5) until all drug bags of the preset prescription are circulated, and finally enters the cycle end state.

[0020] The following description, in conjunction with the accompanying drawings, details the specific scheme of a multi-bag independent control and intelligent circulation system for peritoneal dialysis equipment provided by the present invention.

[0021] Example 1: Please see Figure 1 The diagram shows a system block diagram of a multi-bag independent control and intelligent circulation system for a peritoneal dialysis device according to an embodiment of the present invention. The system includes: a data acquisition module 110, a residue analysis module 120, a residue correction module 130, a feature calibration module 140, and a flushing control module 150.

[0022] The data acquisition module 110 is used to acquire different types of status parameters of the patient in each dialysis cycle of the drug bag compared with several previous dialysis cycles.

[0023] For each dialysis cycle using a medication bag, a built-in high-precision sensor array (including flow meters, temperature probes, and weighing sensors) acquires real-time operational status parameters. These parameters include, but are not limited to, prescription status parameters such as medication concentration, single infusion volume, and preset retention time, as well as patient-preferred parameters such as average pump speed during infusion, actual heating temperature, actual isothermal time, and preset retention time. Simultaneously, to construct a personalized implicit fluid characteristic baseline for each patient, a local or cloud database is accessed to retrieve similar status parameter data from several historical dialysis cycles prior to each medication bag dialysis cycle (e.g., the most recent 30 effective treatment records).

[0024] The residual analysis module 120 is used to determine the basic perfusion residual amount and basic return residual amount of each dialysis cycle based on the structural parameters of the pipeline and the characteristic parameters of the drug solution in each drug solution bag and the waste liquid returned through the peritoneal cavity.

[0025] By using pipeline structural parameters and characteristic parameters of the drug solution in the drug bag and the waste fluid returning through the abdominal cavity, the residual amount of drug solution during the drug injection stage (basic injection residual amount) and the residual amount of waste fluid during the waste fluid return stage (basic return residual amount) are determined respectively. This transforms the fluid retention phenomenon in the pipeline from a qualitative description to a quantitative value, effectively solving the technical problem in existing technologies that leads to blind flushing (incomplete flushing causing cross-contamination, and excessive flushing causing drug waste) due to the lack of residual amount estimation. The residual correction module 130 is used to determine the corrected residual amount for each dialysis cycle of the drug bag based on the basic reflux residual amount and the basic perfusion residual amount adjusted by the flushing effect of waste liquid reflux, as well as the weight change and theoretical ultrafiltration amount before and after each drug bag dialysis cycle.

[0026] Considering that waste liquid recirculation will perform preliminary cleaning of the pipeline, reducing the residual medication in the pipeline, and that theoretical analysis may be inaccurate, sensor feedback must be introduced. This step compensates for the shortcomings of a single theoretical model in describing dynamic fluid retention phenomena by introducing a waste liquid recirculation flushing effect correction and a weighing feedback mechanism. This module first corrects the basic perfusion residue based on fluid mechanics laws using a flushing coefficient. Then, combining the weight change before and after the dialysis cycle with the theoretical ultrafiltration volume, it performs an initial calibration of the theoretical total residue, effectively eliminating system cumulative errors and ensuring that the corrected residue can accurately reflect the current physical retention state within the pipeline.

[0027] The feature calibration module 140 is used to adjust the correction residue based on the difference in state parameters between each dialysis cycle of the drug bag and several previous dialysis cycles, and to determine the feature correction residue for each dialysis cycle of the drug bag.

[0028] Different patients have different operating habits (pump speed, concentration), which can affect the amount of residual medication. The feature calibration module captures the subtle differences in the patient's status parameters in the current dialysis cycle relative to their historical baseline state, incorporates personalized behavioral factors into the residual amount correction analysis, and dynamically adjusts the corrected residual amount to obtain a feature-corrected residual amount that closely matches the current operating conditions. This mechanism allows the flushing strategy to adaptively optimize as the patient's treatment habits evolve, maximizing the personalized adaptability of dialysis operations while ensuring no cross-contamination of medication.

[0029] The flushing control module 150 is used to determine the target flushing volume after each dialysis cycle of each drug bag based on the residual amount of feature correction and the concentration gradient difference between two adjacent cycles of drug solution, and to control the next drug bag to output the target flushing volume of drug solution to flush the pipeline, and to guide the generated flushing waste liquid to the previous drug bag to start the next drug bag dialysis cycle.

[0030] Considering the risks posed by high-concentration residue to low-concentration perfusion, the target flushing volume is adaptively determined by combining the characteristic-corrected residual amount with the osmotic pressure risk difference between the drug concentration gradients of two adjacent dialysis cycles. This ensures that high-risk residues are completely replaced while avoiding drug waste. Simultaneously, through precise control of a multi-way valve, the generated flushing waste liquid is diverted to the emptied drug bag from the previous cycle, achieving intelligent closed-loop control with dual-use functionality and no cross-contamination.

[0031] Preferably, in some possible implementations of the embodiments of the present invention, the method for obtaining the basic infusion residual amount and the basic reflux residual amount includes: Obtain the inner surface area of ​​the tube, the adsorption coefficient of the tube material, the liquid film thickness, and the density of the drug solution in each drug bag and the density of the waste liquid returned through the peritoneum. Record the density of the drug solution in each drug bag and the density of the waste liquid returned through the peritoneum as the analytical density. Take the product of the inner surface area of ​​the tube, the analytical density, and the liquid film thickness of each drug bag as the liquid film residue. Take the product of the inner surface area of ​​the tube and the adsorption coefficient of the tube material as the adsorption residue. Take the sum of the liquid film residue and the adsorption residue as the baseline residue for each drug bag dialysis cycle. Take the baseline residues corresponding to the drug solution in each drug bag and the waste liquid returned through the peritoneum as the baseline perfusion residue and baseline return residue for each drug bag dialysis cycle, respectively.

[0032] It should be noted that the inner surface area of ​​the pipe Where d is the inner diameter of the pipe and L is the effective length of the pipe, both in centimeters. The pipe adsorption coefficient can be determined based on the pipe material (e.g., silicone or PVC), and the unit is usually 1. Before participating in the calculation, it is necessary to... Convert to The liquid film thickness needs to be selected based on the viscosity characteristics of the liquid flowing through the pipeline. A film thickness of 20 micrometers is used for high-viscosity liquids, and 5 micrometers for low-viscosity liquids. Micrometers must be converted to centimeters before calculation. The system monitors the density of the medicine in each medicine bag and the density of the waste liquid after peritoneal reflux. Both densities are expressed in centimeters. .

[0033] Considering that after the medication is emptied from the pipeline, a uniform liquid film will form on the inner wall of the pipe due to surface tension and viscosity, some of this residue can be washed away by gravity or flow rate. The liquid film residue represents the physical residue mass formed due to liquid adhering to the pipe wall surface and unable to be emptied by gravity. Considering that the surface of the pipeline material is not perfectly smooth, and that polymer materials can adsorb specific molecules in the medication, this residue is usually difficult to wash away; the adsorption residue represents the amount of microscopic adsorption of medication molecules by the pipeline material itself. The basic residue obtained by adding the liquid film residue and the adsorption residue represents the inherent and unavoidable residue state in the pipeline after a single fluid delivery process, providing a quantitative benchmark for subsequent dynamic flushing strategies. Liquid residue will remain in the medication filling stage and the waste liquid return stage of each medication bag's dialysis cycle. The basic filling residue corresponds to the medication filling stage, and the basic return residue corresponds to the waste liquid return stage.

[0034] In this embodiment of the invention, the formula for calculating the theoretical ultrafiltration capacity of each dialysis cycle of the drug bag is as follows: In the formula, The theoretical ultrafiltration capacity for each dialysis cycle of the drug bag; The perfusion volume for each dialysis cycle of the drug bag; Density of the liquid in each medicine bag; Waste liquid density for each dialysis cycle of each drug bag; The preset minimum positive number is 0.001 to prevent the fraction from being meaningless due to a zero denominator. Specifically, the weight of each medication bag at the start and end of medication infusion is obtained. The ratio of the difference between the weights of the medication bags before and after infusion to the medication density is used as the infusion volume for each medication bag dialysis cycle. The weights of the two medication bags can be measured using a high-precision weighing sensor.

[0035] It should be noted that since the drug solution only undergoes volume transfer during the infusion process and its physical properties remain unchanged, the ratio of the change in weight of the drug bag before and after infusion to the density of the drug solution can provide a precise estimate of the actual infusion volume. This eliminates potential pumping errors that might arise from preset infusion volumes. Based on the principles of solute mass conservation and volume balance, the theoretical ultrafiltration volume generated by each dialysis cycle of the drug bag is calculated. Quantitative analysis was performed. During peritoneal dialysis, the dialysate and the body's blood undergo bidirectional material exchange through the peritoneum: on the one hand, excess water in the body is driven by osmotic pressure to enter the peritoneal cavity through ultrafiltration, leading to an increase in dialysate volume; on the other hand, metabolic waste (such as urea and creatinine) and solutes such as glucose undergo diffusion exchange under a concentration gradient, resulting in a slight change in dialysate density. To establish a calculable engineering model, this embodiment adopts a simplified material balance assumption: that is, ignoring the total mass fluctuation caused by trace solute exchange, it is approximately assumed that the total mass of solute remains constant before and after dialysis, with only the solvent (water) undergoing a net transfer. Based on this assumption, the following mass balance equation is constructed: ,in, Represents the total mass of the returned waste liquid. This represents the total mass of the medication injected into the peritoneal cavity. This represents the quality of purified water entering the peritoneal cavity through ultrafiltration (the density of the water is approximately 1 gram per milliliter). It can provide a preliminary assessment of the patient's dialysis dehydration status and offer a reference for subsequent residual volume adjustments.

[0036] Preferably, in some possible implementations of the embodiments of the present invention, the method for obtaining the corrected residual amount includes: determining the flushing residual coefficient using the waste liquid reflux rate of each drug bag dialysis cycle; calculating the product of the basic perfusion residual amount and the flushing residual coefficient as the theoretical perfusion residual amount for each drug bag dialysis cycle; taking the sum of the theoretical perfusion residual amount and the basic reflux residual amount for each drug bag dialysis cycle as the theoretical total residual amount; obtaining the drug bag increment after each drug bag dialysis cycle; taking the difference between the theoretical ultrafiltration amount and the drug bag increment for each drug bag dialysis cycle as the actual residual amount; and performing a weighted summation of the theoretical total residual amount and the actual residual amount to obtain the corrected residual amount for each drug bag dialysis cycle.

[0037] It should be noted that, in this embodiment of the invention, a quantitative mapping relationship between the waste liquid recirculation velocity and the scouring residue coefficient is established through numerous prior fluid dynamics experiments. This mapping relationship is based on the following physical facts: the waste liquid has a certain tangential stress when flowing through the pipeline, which can carry away some of the residual liquid film adhering to the pipe wall; the higher the flow velocity, the stronger the shear stress, the better the residue removal effect, and the smaller the corresponding scouring residue coefficient. The specific experimental process is as follows: First, under several set flow rate ranges (e.g., 50 to 100 ml / min, 100 to 150 ml / min, 150 to 200 ml / min), the experimental pipeline is filled with a drug solution of known density and liquid film thickness, and the basic recirculation residue in this initial state is accurately calculated; then, the recirculation pump is started to flush the pipeline with waste liquid at a constant flow rate. After flushing, the actual remaining mass of the drug solution in the pipeline was measured using a precision weighing method or microfluidic analysis, and recorded as the theoretical residual amount. The ratio of the theoretical residual amount to the baseline residual amount under the initial conditions was taken as the flushing residual coefficient at that flow rate. To ensure data reliability, the experiment was repeated 10 times for each flow rate gradient, and the arithmetic mean was taken as the standard flushing residual coefficient for that flow rate range. The standard flushing residual coefficient of the flow rate range in which the waste liquid return rate of each drug bag dialysis cycle falls was taken as the flushing residual coefficient for that waste liquid return rate.

[0038] The theoretical residual amount represents the injected medication that remains in the pipeline after the flushing effect of the waste liquid reflux stage. Since the residual medication adsorbed in the pipeline is usually difficult to flush away, the basic reflux residual amount remains essentially unchanged after the flushing effect. The sum of the two, i.e., the theoretical total residual amount, reflects the total mass of mixed medication and waste liquid retained in the pipeline due to incomplete fluid dynamic flushing after the waste liquid reflux cycle ends. Using a high-precision weighing sensor, the weight m1 of each medication bag before the start of the dialysis cycle and the weight m2 of the medication bag after the end of the dialysis cycle (i.e., after the waste liquid reflux) are obtained, resulting in the medication bag increment as m2-m1. Considering that this increment includes water produced by human ultrafiltration, a theoretical ultrafiltration amount is introduced for correction. That is, the difference between the theoretical ultrafiltration amount and the medication bag increment is taken as the true residual amount, characterizing the actual physical liquid volume deviation retained in the pipeline and the dead zone of the heating bag, excluding human metabolic factors. Finally, in order to balance the stability of theoretical calculations and the accuracy of actual feedback, the theoretical total residue and the actual physical residue are weighted and fused. This makes the residue after the combined fluid dynamics model prediction and sensor measurement data feedback a high-confidence control basis for subsequent flushing strategies.

[0039] In one specific implementation of this invention, the corrected residual amount is expressed by the formula: In the formula, Corrected residual amount for each dialysis cycle of the drug bag; The baseline perfusion residual volume for each dialysis cycle of the drug bag; The scouring residue coefficient is determined by the waste liquid reflux rate for each dialysis cycle of the drug bag; The theoretical residual perfusion volume for each dialysis cycle of the drug bag; The baseline reflux residue for each dialysis cycle of the drug bag; The theoretical total residual amount for each dialysis cycle of the drug bag; The increment of the medication bag after each dialysis cycle; The theoretical ultrafiltration capacity for each dialysis cycle of the drug bag; The actual residual amount for each dialysis cycle in each drug bag; and These are preset weighting coefficients.

[0040] In this embodiment of the invention, a preset weighting coefficient is used. and The value of is set based on the trade-off between the stability of the theoretical model and the sensitivity of sensor feedback in the system control strategy. Typically, to ensure the robustness of residual estimation, a higher weight is assigned to the computational part of the theoretical model, i.e., ... The value is set to 0.6; correspondingly, in order to introduce the necessary real-time error correction, a lower weight is assigned to the sensor feedback part, i.e., a setting is made. The value is 0.4 and satisfies Implementers can make adaptive adjustments according to specific requirements.

[0041] Preferably, in some possible implementations of the embodiments of the present invention, the method for obtaining the feature correction residual amount includes: calculating the arithmetic mean of the same type of state parameters for several dialysis cycles prior to each drug bag dialysis cycle, as the baseline state value for each type; calculating the parameter difference value between the state parameters of each type in each drug bag dialysis cycle and the baseline state value; obtaining the weight of the state parameters of each type using a pre-built grey relational model; calculating the product of the parameter difference value of the state parameters of each type in each drug bag dialysis cycle and the weight, and summing the products corresponding to the state parameters of all types as the state difference degree of the corresponding drug bag dialysis cycle; and weighting the correction residual amount using the state difference degree to obtain the feature correction residual amount for each drug bag dialysis cycle.

[0042] It should be noted that perfusion volume, indwelling time, pump rate, and heating temperature are continuous parameters, while drug concentration and actual isothermal time are discrete parameters. For each type of state parameter, its arithmetic mean (or mode, for discrete parameters) is calculated as the baseline state value for that type. This represents the stable behavioral pattern formed by the patient for specific parameters during long-term dialysis treatment and is used to identify whether the current treatment procedure deviates significantly from the core reference baseline. The parameter difference between each type of state parameter and the baseline state value quantifies the degree of deviation between the current procedure and the patient's long-term habits.

[0043] In this embodiment of the invention, the method for obtaining the parameter difference value is as follows: all types of state parameters include continuous parameters and discrete parameters; for continuous parameters, the ratio of the absolute difference between each type of state parameter and the baseline state value as the numerator, and the range of the corresponding type of state parameter and a preset minimum positive number as the denominator, is used as the parameter difference value; for discrete parameters, when the absolute difference between each type of state parameter and the baseline state value is 0, the parameter difference value is set to 0; when the absolute difference between each type of state parameter and the baseline state value is within a preset range, the parameter difference value is set to a preset value; when the absolute difference between each type of state parameter value and the baseline state value exceeds the preset range, the parameter difference value is set to 1. For example, the discrete parameter of drug concentration typically has fixed values ​​such as 1.5%, 2.5%, and 4.25%. The preset range is set as "concentration specification difference within..." If the absolute difference between the current concentration and the historical baseline concentration is within this range, it is judged as a slight deviation, and the parameter difference value is set to the preset value of 0.5. If the absolute difference exceeds this range, it is judged as a significant deviation, and the value is set to 1.

[0044] In a specific embodiment of the present invention, a grey relational analysis algorithm is used to deeply mine historical treatment cycle data to quantify the intrinsic influence weights of different types of state parameters on changes in basal perfusion and basal reflux residual volumes. First, a dimensionless data matrix is ​​constructed based on a preset historical experimental dataset (containing actual residual measurements under different combinations of state parameters); each type of state parameter is used as an independent variable sequence, and the corresponding actual residual volume is used as a dependent variable reference sequence. All data are mean-normalized to eliminate the influence of different physical dimensions. Then, the absolute difference between each independent variable sequence and the dependent variable reference sequence is calculated to obtain a difference sequence. The global maximum and minimum differences are determined by comparing the extreme values ​​of all sequences. The grey relational coefficient of each state parameter at different sample points is calculated. Next, the arithmetic mean of all correlation coefficients for each type of state parameter is taken to obtain the overall grey relational degree between the parameter of that type and the residual volume. The correlation degrees of all types are then normalized to their maximum and minimum values ​​to obtain the final state parameter weights, objectively reflecting the sensitivity of parameters such as pump rate and temperature to residual volume fluctuations. The weight of each type of state parameter refers to the state parameter weight calculated above for that type of parameter.

[0045] State variability reflects the overall deviation of a patient's individualized implicit fluid characteristics and treatment parameters from their historical baseline values ​​during the current treatment cycle. The state variability is used to weight the corrected residual amount. In this embodiment, the specific operation involves calculating the sum of the product of the state variability and a preset fine-tuning coefficient for each dialysis cycle using a drug bag, plus a constant 1. The product of this sum and the corrected residual amount is then used as the feature-corrected residual amount. Essentially, this incorporates the deviation between the patient's historical implicit fluid characteristics and current treatment parameters into the residual amount estimation. This allows the feature-corrected residual amount to comprehensively reflect the combined effect of physical residual baselines and individualized behavioral deviations, ensuring that the final flushing strategy not only conforms to fluid dynamics principles but also precisely adapts to the specific conditions of the patient's current treatment, achieving true adaptive intelligent control. The preset fine-tuning coefficient is used to control the gain strength of the residual amount compensation by the state difference degree. Under standard operating conditions, a 10% single deviation is generated by artificially setting state parameters (such as pump speed and temperature), and the growth rate of the actual residual amount in the pipeline is measured at this time. The ratio of the growth rate to the state difference degree is used as the preset fine-tuning coefficient of this coefficient, which is preferably set to 0.1.

[0046] Preferably, in some possible implementations of the embodiments of the present invention, the method for obtaining the target flushing volume includes: selecting the maximum value between the difference between the waste liquid density of each dialysis cycle and the liquid density in the next dialysis bag and zero; using the sum of the product of the maximum value and a preset concentration risk gain factor and a preset baseline flushing ratio as the concentration gradient coefficient; and using the product of the characteristic correction residual amount of each dialysis cycle and the concentration gradient coefficient as the target flushing volume after the end of each dialysis cycle.

[0047] It should be noted that the preset baseline flushing ratio ensures that, under any switching conditions, the physical residues remaining in the tubing receive a basic flushing volume, ensuring basic cleanliness. By calculating the difference between the waste fluid density and the density of the next bag of medication and taking the maximum value after dividing by zero, the system accurately detects high-risk switching scenarios where high-osmolarity waste fluid enters low-osmolarity fresh medication, preventing unintended osmolarity damage to the patient's peritoneum caused by residual high-concentration glucose waste fluid. A preset concentration risk gain factor is introduced to linearly convert the concentration inverse into a flushing increment, allowing the flushing intensity to dynamically evolve with the risk level. By multiplying the highly accurate corrected residual amount with the concentration gradient coefficient characterizing the osmolarity risk level, quantitative and precise control of the flushing operation is achieved. This ensures that, during the switching of multiple bags of medication, high-risk residues in the tubing are completely replaced to below the safe threshold, effectively preventing dialysis complications caused by cross-contamination of medications.

[0048] In this embodiment of the invention, a preset baseline flushing ratio and a preset concentration risk gain factor are determined by combining pipeline dead space volume calibration with clinical flushing experiments. First, by measuring the physical dead space volume of the infusion tubing system from the multi-way valve to the heating bag, and combining this with the fluid dynamics flushing efficiency curve, the minimum flushing ratio required to replace the residual liquid volume in the tubing to a safe residual concentration (e.g., below 0.5%) is determined. The preset baseline flushing ratio is set to twice the minimum flushing ratio to ensure the basic physical replacement effect. Based on the maximum concentration gradient condition (e.g., 4.25% waste liquid to 1.5% drug solution), the minimum flushing volume required to reduce the residual solute concentration to the safe threshold of 0.01% is calculated. The preset concentration risk gain factor is preferably set to 5. This ensures that high-risk residues are completely replaced while avoiding drug waste under low-risk conditions, achieving a balance between therapeutic safety and drug economy.

[0049] It is important to note that pipelines have a regular geometric shape (cylindrical inner cavity), and the flow and residual behavior of fluids within them (such as liquid film adhesion and surface adsorption) follows classical fluid dynamics and materials physics principles. In contrast, heating bags are typically made of flexible membrane materials, and their filling and emptying processes involve complex deformation dynamics. Furthermore, the internal dead zone is significantly affected by random factors such as folding methods and gravity distribution, making it difficult to construct a universal theoretical calculation formula. Secondly, the residual quantity introduced by the residual correction module, based on the weighing sensor, is essentially a comprehensive error term. This term not only covers the pipeline residual error calculated by the theoretical model but also implicitly includes physical retention quantities that cannot be directly modeled, such as heating bag dead zone residue and pumping cumulative error. Therefore, through this combined strategy of pipeline theoretical calculation and overall feedback correction, accurate perception and control of the residual quantity of the entire fluid loop, including the heating bag, can still be achieved without adding additional complex models.

[0050] This invention is now complete.

[0051] Example 2: Figure 2 This is a schematic diagram of a computer device for a multi-bag independent control and intelligent circulation system in a peritoneal dialysis apparatus according to an embodiment of the present invention. For example,... Figure 2 As shown, the computer device includes: a memory 201, a processor 202, and a computer program 203 stored in the memory 201 and running on the processor 202, wherein when the processor 202 executes the computer program 203, the computer device can execute the multi-bag independent control and intelligent circulation system of any of the peritoneal dialysis devices described above.

[0052] Furthermore, embodiments of this application also protect an apparatus that may include a memory and a processor, wherein the memory stores executable program code, and the processor is used to call and execute the executable program code to execute a multi-bag independent control and intelligent circulation system for a peritoneal dialysis device provided in embodiments of this application.

[0053] This embodiment can divide the device into functional modules based on the above method example. For example, each module can correspond to a separate function, or two or more functions can be integrated into one processing module. The integrated module can be implemented in hardware. It should be noted that the module division in this embodiment is illustrative and only represents one logical functional division. In actual implementation, there may be other division methods.

[0054] It should be understood that the device provided in this embodiment is used to execute the multi-bag independent control and intelligent circulation system of the peritoneal dialysis device described above, and therefore can achieve the same effect as the above implementation method.

[0055] When using integrated units, the device may include a processing module and a storage module. When applied to a workpiece, the processing module can be used to control and manage the workpiece's operations. The storage module can be used to support the execution of program code by the workpiece.

[0056] The processing module may be a processor or a controller, which can implement or execute various exemplary logic blocks, modules, and circuits as disclosed in this application. The processor may also be a combination of computing functions, such as a combination of one or more microprocessors, a combination of digital signal processing (DSP) and microprocessors, etc., and the storage module may be a memory.

[0057] Example 3: This embodiment also provides a computer-readable storage medium storing computer program code. When the computer program code is run on a computer, the computer executes the above-described related method steps to realize the multi-bag independent control and intelligent circulation system of the peritoneal dialysis device provided in the above embodiment.

[0058] In this embodiment, the device and computer-readable storage medium are used to execute the corresponding system provided above. Therefore, the beneficial effects that can be achieved can be referred to the beneficial effects of the corresponding system provided above, and will not be repeated here.

[0059] It should be noted that the order of the above embodiments of the present invention is merely for descriptive purposes and does not represent the superiority or inferiority of the embodiments. The processes depicted in the accompanying drawings do not necessarily require a specific or sequential order to achieve the desired result. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0060] The various embodiments in this specification are described in a progressive manner. The same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on describing the differences from other embodiments.

[0061] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A multi-bag independent control and intelligent circulation system for a peritoneal dialysis device, the peritoneal dialysis device comprising a plurality of drug solution bags connected by multi-channel tubing and a patient-end interface, characterized in that, The system includes: The data acquisition module is used to acquire different types of status parameters of the patient in each dialysis cycle of the drug bag compared with the previous several dialysis cycles; The residual analysis module is used to determine the basic perfusion residual amount and basic return residual amount of each dialysis cycle based on the structural parameters of the pipeline and the characteristic parameters of the drug solution in each drug solution bag and the waste liquid returned through the peritoneal cavity. The residual correction module is used to determine the corrected residual amount for each dialysis cycle of the drug bag based on the basic reflux residual amount and the scouring effect of the waste liquid reflux, as well as the weight change and theoretical ultrafiltration amount before and after each dialysis cycle of the drug bag. The feature calibration module is used to adjust the correction residue based on the difference in state parameters between each dialysis cycle of the drug bag and several previous dialysis cycles, and to determine the feature correction residue for each dialysis cycle of the drug bag. The flushing control module is used to determine the target flushing volume after each dialysis cycle of each drug bag based on the residual amount corrected by the characteristics and the concentration gradient difference between two adjacent cycles of drug solution, and to control the next drug bag to output the target flushing volume of drug solution to flush the pipeline, and to guide the generated flushing waste liquid to the previous drug bag to start the next dialysis cycle of the drug bag.

2. The multi-bag independent control and intelligent circulation system for a peritoneal dialysis device according to claim 1, characterized in that, The determination of the baseline perfusion residual volume and baseline reflux residual volume for each dialysis cycle of the drug bag includes: The inner surface area of ​​the tube, the adsorption coefficient of the tube, the thickness of the liquid film, and the density of the liquid in each medicine bag and the density of the waste liquid returned through the abdominal cavity were obtained. The density of the medicine in each medicine bag and the density of the waste liquid returned through the abdominal cavity are recorded as the analytical density. The product of the inner surface area of ​​each drug bag, the analytical density, and the liquid film thickness is taken as the liquid film residue. The product of the inner surface area of ​​each medicine bag and the adsorption coefficient of the tube is taken as the adsorption residue. The sum of the liquid film residue and the adsorption residue is used as the basic residue for each dialysis cycle of the drug bag; The baseline residual amounts corresponding to the medication in each medication bag and the waste fluid returned through the peritoneal cavity are used as the baseline perfusion residual amount and baseline return residual amount for each medication bag dialysis cycle, respectively.

3. The multi-bag independent control and intelligent circulation system for a peritoneal dialysis device according to claim 2, characterized in that, The method for obtaining the theoretical ultrafiltration capacity includes: The formula for calculating the theoretical ultrafiltration capacity of each dialysis cycle using a drug bag is: In the formula, The theoretical ultrafiltration capacity for each dialysis cycle of the drug bag; The perfusion volume for each dialysis cycle of the drug bag; Density of the liquid in each medicine bag; Waste liquid density for each dialysis cycle of each drug bag; It is a preset minimum positive number.

4. The multi-bag independent control and intelligent circulation system for a peritoneal dialysis device according to claim 1, characterized in that, The determination of the corrected residual amount for each dialysis cycle of the drug bag includes: The scouring residual coefficient is determined by the waste liquid reflux rate of each dialysis cycle of the drug bag; the product of the basic perfusion residual amount and the scouring residual coefficient is calculated as the theoretical perfusion residual amount of each dialysis cycle of the drug bag. The sum of the theoretical perfusion residue for each dialysis cycle of the drug bag and the basic reflux residue is taken as the theoretical total residue. Obtain the volume increment of the drug bag after each dialysis cycle; take the difference between the theoretical ultrafiltration volume and the volume increment of the drug bag for each dialysis cycle as the actual residual amount; The corrected residual amount for each dialysis cycle of the drug solution bag is obtained by weighted summation of the theoretical total residual amount and the actual residual amount.

5. The multi-bag independent control and intelligent circulation system for a peritoneal dialysis device according to claim 1, characterized in that, The determination of the characteristic corrected residual amount for each dialysis cycle of the drug bag includes: Calculate the arithmetic mean of the same type of state parameters for several dialysis cycles prior to each drug bag dialysis cycle, and use it as the baseline state value for each type; Calculate the parameter difference between each type of state parameter and the baseline state value for each dialysis cycle of the drug bag; obtain the weight of each type of state parameter using a pre-built grey relational model; Calculate the product of the parameter difference value of each type of state parameter for each drug bag dialysis cycle and the weight, and sum the products corresponding to all types of state parameters as the state difference degree of the corresponding drug bag dialysis cycle; The corrected residual amount is weighted using the state difference degree to obtain the characteristic corrected residual amount for each dialysis cycle of the drug bag.

6. The multi-bag independent control and intelligent circulation system for a peritoneal dialysis device according to claim 5, characterized in that, The calculation of the parameter difference between each type of state parameter and the baseline state value for each dialysis cycle of the drug bag includes: All types of state parameters include continuous parameters and discrete parameters; For continuous parameters, the absolute difference between each type of state parameter and the reference state value is used as the numerator, and the ratio of the range of the corresponding type of state parameter to a preset minimum positive number is used as the denominator, which is the parameter difference value. For discrete parameters, when the absolute difference between each type of state parameter and the baseline state value is 0, the parameter difference value is set to 0; When the absolute difference between each type of state parameter and the baseline state value is within a preset range, the parameter difference value is set to the preset value. When the absolute difference between the state parameter value of each type and the baseline state value exceeds a preset range, the parameter difference value is set to 1.

7. The multi-bag independent control and intelligent circulation system for a peritoneal dialysis device according to claim 1, characterized in that, Determining the target flush volume after each dialysis cycle of the medication bag includes: The difference between the waste liquid density of each dialysis cycle and the liquid density of the next dialysis bag is selected as the maximum value between zero and the maximum value. The sum of the product of the maximum value and the preset concentration risk gain factor and the preset baseline flushing ratio is used as the concentration gradient coefficient. The product of the characteristic correction residue of each drug bag dialysis cycle and the concentration gradient coefficient is used as the target flushing volume after each drug bag dialysis cycle.

8. The multi-bag independent control and intelligent circulation system for a peritoneal dialysis device according to claim 7, characterized in that, The preset concentration risk gain factor is 5.

9. The multi-bag independent control and intelligent circulation system for a peritoneal dialysis device according to claim 5, characterized in that, The weighting of the corrected residual amount using the degree of state difference includes: Calculate the sum of the product of the state difference degree and the preset fine-tuning coefficient for each dialysis cycle of the drug bag and the constant 1. Multiply the sum by the corrected residual amount as the characteristic corrected residual amount.

10. The multi-bag independent control and intelligent circulation system for a peritoneal dialysis device according to claim 3, characterized in that, The method for obtaining the perfusion volume of each dialysis cycle in the drug bag includes: Obtain the weight of each medicine bag at the start of medicine infusion and the weight of each medicine bag at the end of medicine infusion; The ratio of the difference between the weight of the dialysis bag before and after the infusion begins to the density of the dialysis bag is used as the infusion volume for each dialysis cycle.

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