Automatic intestinal lavage instrument system based on multi-dimensional data fusion analysis and method thereof

Abstract

The invention relates to the technical field of intelligent intestinal lavage instruments, and discloses an automatic intestinal lavage instrument system based on multi-dimensional data fusion analysis and a method thereof.The system comprises a water inlet execution module, a water outlet execution module, a data acquisition module and a man-machine interaction module; the intelligent decision-making module is in communication connection with the water inlet execution module, the water outlet execution module, the data acquisition module and the man-machine interaction module. The method corresponds to the system. According to the invention, multi-dimensional data such as the water inlet pressure, the water outlet pressure, the water inlet flow and the water outlet flow can be fused in real time, liquid balance is calculated, and the pressure risk is evaluated; based on the fusion analysis result, a comprehensive control instruction can be dynamically generated and executed, self-adaptive precise adjustment of the water inlet speed, the water outlet speed and the treatment circulation node is achieved, the abnormal condition can be responded in time, risk prediction and prospective regulation and control can be conducted based on an individualized model, and the system is suitable for popularization and application. Therefore, the safety, the individuation level and the overall automation efficiency of the intestinal lavage treatment process are improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of intelligent intestinal lavage apparatus, and particularly relates to an automatic intestinal lavage apparatus system based on multi-dimensional data fusion analysis and a method thereof. BACKGROUND

[0002] The existing automatic intestinal lavage apparatus usually adopts a preset program or is controlled based on a single parameter threshold (such as an upper pressure limit), and has a limited intelligent level. Such apparatuses generally have the following disadvantages: first, the control logic thereof is relatively isolated, and multi-dimensional information such as water inflow and outflow speed, pressure, and liquid balance cannot be fused and comprehensively analyzed in real time, so that the system cannot accurately perceive the dynamic physiological state changes in the treatment process; second, treatment parameters (such as a pressure safety threshold and a single infusion volume) are mostly fixed values or need to be set by an operator based on experience, and cannot be individually adapted according to physiological differences of different patients, so that there is a treatment risk or an impact on comfort; and finally, the whole control process is mostly open-loop or simple closed-loop, and lacks the ability of predictive decision and adaptive adjustment based on real-time comprehensive evaluation, for example, cannot actively intervene before the actual occurrence of liquid retention risk.

[0003] Therefore, a new automatic intestinal lavage system capable of realizing multi-parameter deep fusion, individual adaptation, and full-process intelligent closed-loop control is urgently needed to fundamentally improve the safety, effectiveness, and automation level of treatment. SUMMARY

[0004] The present application aims to provide an automatic intestinal lavage apparatus system based on multi-dimensional data fusion analysis and a method thereof to solve the technical problems proposed in the background.

[0005] To achieve the above-mentioned purpose, the present application discloses the following technical solutions: In a first aspect, the present application discloses an automatic intestinal lavage apparatus system based on multi-dimensional data fusion analysis, comprising a water inflow execution module, a water outflow execution module, a data acquisition module, and a human-computer interaction module, and further comprising: An intelligent decision module in communication connection with the water inflow execution module, the water outflow execution module, the data acquisition module, and the human-computer interaction module; wherein the intelligent decision module comprises: A data fusion analysis unit configured to: receive a real-time data stream from the data acquisition module, the real-time data stream comprising at least water inflow pressure, water outflow pressure, water inflow flow rate, and water outflow flow rate; calculate a real-time liquid balance value based on the water inflow flow rate and the water outflow flow rate; and perform pressure risk assessment based on the water inflow pressure, the water outflow pressure, and a preset individualized pressure safety model; an adaptive control unit configured to generate a comprehensive control instruction according to the real-time liquid balance value and the pressure risk assessment result output by the data fusion analysis unit, the comprehensive control instruction being used to dynamically adjust the water inflow speed of the water inflow execution module and the water outflow speed of the water outflow execution module and to determine the start-stop timing of the next water inflow cycle; The intelligent decision-making module constitutes a full-closed-loop adaptive control for the bowel cleansing process through the cooperative operation of the data fusion analysis unit and the adaptive control unit.

[0006] Optionally, the data fusion analysis unit is further configured to perform construction of an intestinal compliance model, the construction of the intestinal compliance model comprising: During the initial water inflow stage, intestinal pressure change data under different water inflow volumes are recorded; According to the corresponding relationship between the intestinal pressure change data and the water inflow volume, an intestinal compliance curve reflecting the elastic characteristics of the intestinal tract of the current patient is fitted and generated; The pressure early warning threshold of the individualized pressure safety model is dynamically adjusted based on the intestinal compliance curve.

[0007] Optionally, the data fusion analysis unit performs liquid retention risk prediction based on the intestinal compliance curve and the real-time liquid balance value. When it is predicted that there is a liquid retention risk, the comprehensive control instruction generated by the adaptive control unit comprises: reducing the water inflow speed and increasing the water outflow negative pressure, and prohibiting the start of a new water inflow cycle until the real-time liquid balance value returns to a safe range.

[0008] Optionally, the logic of the adaptive control unit for generating the comprehensive control instruction comprises a liquid balance closed-loop control sub-logic, the liquid balance closed-loop control sub-logic comprising: setting a liquid balance target interval; comparing the real-time liquid balance value with the target interval; if the real-time liquid balance value continuously exceeds the upper limit of the target interval, generating an instruction to increase the power of the negative pressure pump of the water outflow execution module; if the real-time liquid balance value continuously falls below the lower limit of the target interval, generating an instruction to suspend water inflow and extend the water outflow time.

[0009] Optionally, the intelligent decision-making module further comprises a safety decision unit configured to receive the pressure risk assessment result output by the data fusion analysis unit and to receive the bowel cleansing liquid temperature data from the data acquisition module. When any of the following conditions is met, a first-level safety strategy is triggered, and the adaptive control unit generates an instruction to immediately stop all execution modules: Condition A: the pressure risk assessment result is high risk; Condition B: the temperature of the cleansing liquid exceeds 41℃ or is lower than 38℃; When the following condition is met, a secondary safety strategy is triggered, and the adaptive control unit generates an instruction to reduce the water inflow speed and issue a warning: Condition C: the negative offset rate of the real-time liquid balance value exceeds a set threshold.

[0010] Optionally, the human-computer interaction module is configured to input patient individual parameters, the patient individual parameters at least including body weight; The data fusion analysis unit is further configured to: according to the body weight, calculate an initial single water inflow upper limit based on a preset mapping relationship between body weight and single safety water inflow; and during the treatment, dynamically correct the single water inflow upper limit according to the real-time liquid balance value and the pressure risk assessment result.

[0011] Optionally, when dynamically correcting the single water inflow upper limit, the data fusion analysis unit performs the following steps: Obtain the pressure stability and liquid balance compliance score of the current treatment cycle; If the score is lower than the adaptive threshold, the single water inflow upper limit of the next cycle is lowered by a preset step size; If the scores of consecutive multiple cycles are all higher than the optimization threshold, the single water inflow upper limit is increased by a preset step size until the theoretical maximum value calculated based on the body weight is reached.

[0012] Optionally, the water inflow execution module includes a positive pressure pump, a proportional valve, and a water inflow warming unit, the adaptive control unit cooperatively controls the water inflow speed and pressure by adjusting the opening of the proportional valve and the rotating speed of the positive pressure pump, and maintains the liquid temperature at a set value by controlling the working power of the water inflow warming unit. The water outflow execution module includes a negative pressure pump and a waste liquid temporary storage container, the rotating speed of the negative pressure pump is steplessly adjusted by the adaptive control unit according to the real-time liquid balance value and the water outflow pressure.

[0013] Optionally, the data acquisition module includes: A first pressure sensor and a second pressure sensor are arranged on the water inflow passage and the water outflow passage respectively, for acquiring the water inflow pressure and the water outflow pressure; A first flow meter and a second flow meter are arranged on the water inflow passage and the water outflow passage respectively, for acquiring the water inflow flow and the water outflow flow; A temperature sensor is arranged at the outlet of the water inflow warming unit, for acquiring the temperature of the cleansing liquid; The data fusion analysis unit synchronously acquires data of each sensor at a fixed sampling period, and performs timestamp alignment to form the real-time data stream.

[0014] In a second aspect, the application provides a method applied to the automatic colon cleansing instrument system based on multi-dimensional data fusion analysis as described above, which is executed by the intelligent decision module and includes the following steps: A multi-dimensional data acquisition step: synchronously acquiring a real-time data stream of the colon cleansing process by the data acquisition module, the real-time data stream including at least water inlet pressure, water outlet pressure, water inlet flow rate and water outlet flow rate; A data fusion and analysis step: receiving and processing the real-time data stream by the data fusion analysis unit, and performing the following operations: S11-Liquid balance calculation: calculating a real-time liquid balance value based on the water inlet flow rate and the water outlet flow rate in a period; S12-Pressure risk assessment: calling a preset individualized pressure safety model to analyze the water inlet pressure and the water outlet pressure, and generating a pressure risk assessment result; An adaptive closed-loop control step: performing the following operations by the adaptive control unit according to the real-time liquid balance value and the pressure risk assessment result: S21-Control instruction generation: generating a comprehensive control instruction based on the fusion judgment of the real-time liquid balance value and the pressure risk assessment result; S22-Execution and adjustment: sending the comprehensive control instruction to the water inlet execution module and the water outlet execution module to dynamically adjust the water inlet speed and the water outlet speed, and to decide the start-stop timing of the next water inlet cycle.

[0015] Compared with the prior art, the automatic colon cleansing instrument system and method based on multi-dimensional data fusion analysis have at least the following beneficial effects: The multi-dimensional data such as water inlet pressure, water outlet pressure, water inlet flow rate and water outlet flow rate can be fused in real time, and liquid balance can be calculated and pressure risk can be assessed. Based on the fusion analysis result, a comprehensive control instruction can be dynamically generated and executed to realize adaptive and accurate adjustment of the water inlet speed, the water outlet speed and the treatment cycle node. This full-closed-loop intelligent control architecture can not only respond to abnormal conditions in real time, but also predict and prospectively regulate risks based on individualized models, thereby improving the safety, individualization level and overall automation efficiency of the colon cleansing treatment process. BRIEF DESCRIPTION OF DRAWINGS

[0016] To more clearly illustrate the technical solutions 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.

[0017] Figure 1 The diagram shows the structure of an automated colon cleansing system based on multidimensional data fusion analysis, as provided in an embodiment of the present invention. Detailed Implementation

[0018] To facilitate understanding of the technical solutions provided in the embodiments of this application, the background technology involved in the embodiments of this application will be described below.

[0019] Currently used automated colon cleansing devices in clinical practice largely rely on preset fixed programs or single parameter thresholds (such as setting only a pressure upper limit) for their control logic, resulting in significant limitations in their intelligent regulation capabilities. Specifically, the core shortcomings of these devices are reflected in three key aspects: Firstly, the isolation of parameter perception and analysis: existing equipment fails to integrate and process real-time data from multiple dimensions, such as inlet and outlet pressure, inlet and outlet flow rates, which are key parameters during colon cleansing. Instead, it makes independent judgments on individual parameters, resulting in the system's inability to comprehensively and accurately capture the dynamic physiological changes of the patient's intestines during treatment. For example, it is difficult to grasp the balance of fluid inflow and outflow and the overall fluctuation trend of intestinal pressure in real time. Secondly, the treatment parameters are not individually adapted. Core treatment parameters such as pressure safety threshold and single infusion volume are mostly uniform fixed values ​​or need to be manually set by the operator's clinical experience. They cannot be dynamically adjusted according to individual physiological differences such as patient weight and intestinal elasticity. This may lead to treatment risks such as excessive pressure and fluid retention due to improper parameter adaptation, and may also affect treatment comfort and cleaning effect due to unreasonable infusion volume. Third, the passive nature of the control mode: the control process of existing equipment is mostly open-loop control or simple closed-loop control for a single parameter. It lacks the predictive decision-making ability based on comprehensive evaluation of multi-dimensional data, and cannot actively intervene before risks such as fluid retention and abnormal pressure actually occur. It can only respond passively after abnormal situations occur, making it difficult to achieve dynamic optimization of the treatment process.

[0020] Based on the aforementioned shortcomings of existing technologies, there is an urgent need for a new type of automated colon cleansing system that can achieve in-depth multi-parameter fusion analysis, dynamically adapt treatment parameters to individual patient differences, and form a fully intelligent closed-loop control system. This would fundamentally solve the problems of insufficient safety, low personalization, and limited automation efficiency of existing equipment.

[0021] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present application, and not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present application. Secondly, in this document, the term "comprising" is intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements, but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes the element.

[0022] Firstly, this embodiment provides an automated colon cleansing system based on multidimensional data fusion analysis, such as... Figure 1 As shown, it includes an inlet execution module, an outlet execution module, a data acquisition module, and a human-machine interaction module, and also includes an intelligent decision-making module that is communicatively connected to the inlet execution module, the outlet execution module, the data acquisition module, and the human-machine interaction module. The intelligent decision-making module includes: The data fusion and analysis unit is configured to: receive real-time data streams from the data acquisition module, the real-time data streams including at least inlet water pressure, outlet water pressure, inlet water flow rate, and outlet water flow rate; calculate real-time liquid balance values ​​based on inlet water flow rate and outlet water flow rate; and conduct pressure risk assessments based on inlet water pressure, outlet water pressure, and a preset individualized pressure safety model. The adaptive control unit is configured to generate comprehensive control commands based on the real-time liquid balance value and pressure risk assessment results output by the data fusion analysis unit. The comprehensive control commands are used to dynamically adjust the water inlet speed of the water inlet actuator and the water outlet speed of the water outlet actuator, and to determine the start and stop timing of the next water inlet cycle. Furthermore, the intelligent decision-making module, through the coordinated operation of the data fusion analysis unit and the adaptive control unit, constitutes a fully closed-loop adaptive control of the colon cleansing process.

[0023] In practical implementation, the water inlet execution module, water outlet execution module, data acquisition module, and human-machine interaction module can all adopt any of the existing technologies. Among them, the water inlet execution module is mainly used to deliver the colon cleansing fluid to the intestine according to the control instructions; the water outlet execution module is mainly used to discharge and temporarily store the waste fluid in the intestine; the data acquisition module is mainly used to synchronously collect real-time data such as pressure, flow rate, and temperature during the colon cleansing process; the human-machine interaction module is mainly used to display real-time treatment data (such as water inlet pressure and fluid balance value) and receive basic instructions input by the operator. For example, an industrial-grade 10.1-inch capacitive touch screen (model: TFT101-C210) can be used. This model of touch screen has an IP65 waterproof rating, can withstand alcohol disinfection in medical scenarios, and has a touch response time of ≤50ms, which can meet the requirements of rapid parameter input.

[0024] Secondly, the hardware carrier of the intelligent decision-making module adopts an embedded control board, the core of which includes a data fusion analysis unit and an adaptive control unit. The two interact with each other through the onboard SPI bus (communication rate 10Mbps).

[0025] Specifically, the data fusion and analysis unit employs an ARM Cortex-A9 processor (1.2GHz) paired with an 8GB eMMC storage unit. The processor's computing power can meet the real-time processing requirements of 100 sets of multi-dimensional data per second, and the storage unit is used to temporarily store real-time data streams over 12 hours. The real-time liquid balance value is achieved through integral calculation, using the following formula: , in, The real-time liquid balance value at time t (unit: mL) Let τ be the influent flow rate (unit: mL / s). The outflow rate at time τ (unit: mL / s). The initial parameters of the preset individualized pressure safety model are based on the average tolerance pressure of the adult intestine (e.g., influent pressure safety baseline 1.5 kPa, outflow pressure safety baseline -0.8 kPa).

[0026] Furthermore, the adaptive control unit can employ an STM32F407 microcontroller (168MHz clock speed) with 12 PWM output interfaces. It connects to the inlet and outlet execution modules via an RS485 bus (9600bps communication rate), generating comprehensive control commands including PWM signals (for adjusting pump speed and valve opening) and switching signals (for controlling cycle start and stop). Feasibly, in practical applications, the controller command execution delay is ≤20ms to ensure real-time response to the colon cleansing process.

[0027] Based on the above, during the colon cleansing process, the data acquisition module transmits data such as inlet water pressure, outlet water pressure, and inlet / outlet water flow rate to the data fusion analysis unit at fixed intervals. The fusion analysis unit obtains the real-time liquid balance value through integral calculation and assesses the pressure risk in conjunction with an individualized pressure safety model. Based on the above analysis results, the adaptive control unit generates comprehensive control commands for inlet water speed, outlet water speed, and cycle start / stop, and sends them to the inlet water execution module and outlet water execution module, respectively. At the same time, the execution effect of the control commands is fed back to the fusion analysis unit in real time through the data acquisition module, forming a closed-loop process of acquisition-analysis-control-feedback.

[0028] This implementation method enables real-time fusion analysis of multi-dimensional data, avoiding the limitations of single-parameter control; the fully closed-loop adaptive control can dynamically match changes in physiological state during the colon cleansing process, and respond instantly to abnormal pressure, fluid imbalance and other situations, thereby improving treatment safety and automation, and reducing the need for manual intervention.

[0029] Existing automatic colon cleansing equipment often uses a single component (such as a positive pressure pump) to control the water inlet parameters, which makes it difficult to coordinate the water inlet speed and pressure. This can easily lead to problems such as "speed meets the standard but pressure exceeds the limit" or "pressure meets the standard but speed is insufficient". The negative pressure regulation of the water outlet is mostly stepped, which cannot achieve stepless and precise control according to real-time needs, affecting the stability of liquid discharge. Therefore, it is urgent to optimize the structure and control logic of the water inlet and outlet execution modules.

[0030] Therefore, as an optional implementation of this embodiment, the water inlet execution module includes a positive pressure pump, a proportional valve, and a water inlet heating unit. The adaptive control unit controls the water inlet speed and pressure in a coordinated manner by adjusting the opening of the proportional valve and the rotation speed of the positive pressure pump, and maintains the liquid temperature at a set value by controlling the working power of the water inlet heating unit. The water discharge module includes a negative pressure pump and a waste liquid storage container. The speed of the negative pressure pump is steplessly adjusted by the adaptive control unit based on the real-time liquid balance value and the water discharge pressure.

[0031] In practical implementation, for the water inlet actuator module component: ① The positive pressure pump adopts a miniature diaphragm pump of model MP-40, with a rated speed of 0-3000rpm, a rated pressure of 0-80kPa, and a flow range of 0-300mL / min; the adaptive control unit adjusts the pump speed through a PWM signal (frequency 1kHz). For every 100rpm increase in speed, the inlet water flow rate increases by about 10mL / min, and the pressure increases by about 2kPa. This model of pump has a small linearity error, ensuring a stable correspondence between speed and parameters. In practical applications, models such as MP-50 can also be selected, but this application embodiment does not limit this.

[0032] ② The proportional valve adopts an SV-15 electromagnetic proportional valve with an opening adjustment range of 0%-100%, a response time of <50ms, and a working pressure range of 0-100kPa. The adaptive control unit controls the opening through a 0-5V analog voltage signal. For every 10% increase in opening, the inlet water flow rate increases by approximately 8mL / min, and the pressure decreases by approximately 1kPa. Through the coordinated adjustment of "positive pressure pump speed + proportional valve opening", for example, when an inlet water rate of 150mL / min and a pressure of 30kPa are required, the positive pressure pump speed is controlled at 1800rpm (corresponding to a flow rate of 180mL / min and a pressure of 36kPa), and the proportional valve opening is controlled at 75% (corresponding to a decrease in flow rate of 30mL / min and a decrease in pressure of 6kPa), ultimately achieving the target parameters.

[0033] ③ The water inlet heating unit includes a 100W PTC heater (model PTC-100) and a temperature feedback loop, with a set temperature of 39.5℃ (the comfortable temperature for the human intestinal tract); the adaptive control unit controls the heater power through a PID algorithm. When the temperature sensor detects that the liquid temperature is below 39℃, the power is increased to 100%; when the temperature is above 40℃, the power is reduced to 0%; when the temperature is between 39-40℃, the power is adjusted proportionally (e.g., 50% power at 39.2℃).

[0034] For the water outlet execution module components: ① The negative pressure pump adopts the NP-60 brushless negative pressure pump with a rated speed of 0-4000rpm, a negative pressure range of 0 to -80kPa, and a flow rate range of 0-400mL / min. The adaptive control unit sends speed commands through the 485 communication protocol to achieve stepless adjustment from 0 to 4000rpm. For every 200rpm increase in speed, the negative pressure decreases by about 2kPa and the flow rate increases by about 20mL / min, ensuring precise matching of negative pressure and flow rate.

[0035] ② The waste liquid temporary storage container is made of transparent PP material (3mm thick) with a volume of 2000mL. The side wall of the container is equipped with a liquid level sensor (model LS-200). When the liquid level reaches 1800mL (warning level), a signal is sent to the adaptive control unit to trigger the instruction of "pause water discharge and prompt emptying" to prevent waste liquid from overflowing. The PP material is resistant to acid and alkali corrosion, and its transparency makes it easy for operators to observe the liquid level. In practical applications, the container volume can be selected as 1500mL or 2500mL. This application embodiment does not limit this.

[0036] Based on the above, the water inlet execution module achieves precise matching of water inlet speed and pressure through the coordinated control of a positive pressure pump (mainly adjusting flow and pressure) and a proportional valve (fine-tuning flow and pressure); the water inlet heating unit maintains stable liquid temperature through a PID algorithm; the water outlet execution module continuously adjusts the speed of the negative pressure pump to ensure that the negative pressure and flow of the outlet water are adapted to the liquid balance requirements in real time; and the waste liquid temporary storage container prevents overflow through liquid level monitoring, forming a complete water inlet and outlet execution control system.

[0037] Existing automated colon cleansing equipment often suffers from problems such as unreasonable sensor placement (e.g., temperature sensors are far from the water inlet, causing delayed temperature feedback) and asynchronous data sampling (e.g., large time differences between water pressure and flow rate sampling, making matching and analysis impossible). This results in insufficient accuracy and synchronization of the collected real-time data stream, failing to provide a reliable data foundation for subsequent fusion analysis. It is urgent to clarify the sensor placement, type, and data synchronization mechanism.

[0038] Therefore, as an optional implementation method in this embodiment, the data acquisition module includes: The first pressure sensor and the second pressure sensor are respectively installed on the water inlet passage and the water outlet passage to collect the water inlet pressure and the water outlet pressure. The first flow meter and the second flow meter are respectively installed on the inlet passage and the outlet passage to collect the inlet flow rate and the outlet flow rate; A temperature sensor is installed at the outlet of the water inlet heating unit to collect the temperature of the enemas. The data fusion and analysis unit synchronously acquires data from each sensor at a fixed sampling period and aligns the timestamps to form a real-time data stream.

[0039] In practical implementation, the first pressure sensor (for collecting inlet water pressure) is a PT-124G-111 diffused silicon pressure sensor with a measurement range of 0-100 kPa. It is installed in the pipeline between the proportional valve outlet and the intestinal connecting pipe in the inlet water passage, no more than 10 cm from the proportional valve outlet, ensuring that the collected pressure accurately reflects the pressure of the liquid entering the intestine and avoiding pressure loss errors caused by excessively long pipelines. The second pressure sensor (for collecting outlet water pressure) is a PT-124G-011 negative pressure sensor with a measurement range of 0 to -100 kPa. It is installed in the pipeline between the intestinal connecting pipe and the negative pressure pump inlet in the outlet water passage, no more than 10 cm from the outlet of the intestinal connecting pipe, ensuring that the collected pressure accurately reflects the pressure of the liquid being discharged from the intestine.

[0040] The first flow meter (for collecting influent flow) is a miniature turbine flow meter, model FL-801, with a measurement range of 0-500 mL / min and an output pulse signal (1000 pulses per liter of liquid). It is installed on the pipeline between the positive pressure pump outlet and the proportional valve inlet in the influent path. This location accurately collects the total influent flow before the proportional valve adjustment, avoiding the influence of proportional valve opening changes on flow measurement. The second flow meter (for collecting effluent flow) is a miniature turbine flow meter, model FL-802, with a measurement range of 0-600 mL / min and an output pulse signal (1000 pulses per liter of liquid). It is installed on the pipeline between the negative pressure pump outlet and the waste liquid temporary storage container inlet in the effluent path, ensuring that the actual discharged waste liquid flow is collected, avoiding interference from negative pressure fluctuations on flow measurement.

[0041] The temperature sensor is a DS18B20 digital temperature sensor with a measurement range of -55℃ to 125℃ and a sampling period of 1 second. It is installed on the pipeline at the outlet of the water inlet heating unit, no more than 5cm away from the heater outlet, to ensure that the temperature of the liquid that is about to enter the intestine after heating is collected, and to avoid temperature deviation caused by heat dissipation from the pipeline.

[0042] In addition, the data fusion analysis unit is set to a fixed sampling period of 100ms (i.e., 10 samples per second). Within each sampling period, the output signals of each sensor are read simultaneously through a multi-channel data acquisition card (model DAQ-2004), and a unified timestamp (accurate to milliseconds) is added to each data channel. If the data of a certain sensor channel is not returned in time within the sampling period (e.g., due to communication delay), the data of the previous period is used as a substitute and marked as "to be verified". The next period will prioritize updating the data of that channel to ensure the time consistency and integrity of the real-time data stream.

[0043] Based on the above, the data acquisition module ensures that the collected pressure, flow, and temperature data accurately reflect the actual state of the colon cleansing process by precisely placing each sensor at key locations in the inlet and outlet water passages. Furthermore, through a fixed sampling period and timestamp alignment mechanism, it achieves synchronous acquisition of multi-dimensional data, providing an accurate, complete, and synchronized real-time data stream foundation for the data fusion and analysis unit.

[0044] By employing this implementation method, the precise arrangement of sensors reduces the acquisition errors of pressure, flow, and temperature data, while the data synchronization mechanism ensures that the time deviation of multi-dimensional data is reduced, thus guaranteeing the accuracy of subsequent data fusion analysis and avoiding the risk of misjudgment due to data asynchrony.

[0045] Conventional individualized stress safety models use fixed initial thresholds, which cannot adapt to the different intestinal elasticities of patients (such as the significant difference in intestinal compliance between children and adults). This can easily lead to stress warning thresholds that are too high or too low, increasing treatment risks. Therefore, it is necessary to construct an intestinal compliance model to achieve individualized dynamic adjustment of stress warning thresholds.

[0046] Therefore, as an optional implementation of this embodiment, the data fusion analysis unit is further configured to: construct a gut compliance model, wherein the steps for constructing the gut compliance model include: During the initial water intake phase, data on changes in intestinal pressure were recorded under different water intake volumes. Based on the correlation between changes in intestinal pressure and the volume of water intake, an intestinal compliance curve reflecting the current intestinal elasticity characteristics of the patient is generated by fitting the data. The individualized stress safety model's stress warning threshold is dynamically adjusted based on the gut compliance curve.

[0047] In practice, during the initial water intake phase, the water intake rate is fixed at 50 mL / min (to avoid flow rate fluctuations affecting the accuracy of pressure data). The water volume is gradually increased in increments of 20 mL, with a 3-second stabilization period after each increase before recording the current intestinal pressure data. Intestinal pressure is collected by a pressure sensor (model: MPX5700, range 0-5 kPa, accuracy ±1.5%FS) located at the end of the intestinal insertion tube. This sensor is small (3 mm in diameter) and can be integrated into the insertion tube to avoid additional irritation to the intestine. Other models can be used in practical applications, but this embodiment does not limit the choice. The total volume during the initial water intake phase does not exceed 100 mL to prevent excessive water intake from causing discomfort.

[0048] Secondly, a two-segment nonlinear fitting method is used to fit the compliance curve, and the fitting formula is as follows: , in, For volume Intestinal pressure at time (unit: kPa). The inlet water volume (unit: mL). The volume at the inflection point of intestinal elasticity (unit: mL). for Linearity coefficients (unit: kPa / mL) at that time. for The quadratic coefficient at time (unit: kPa / mL) 2 ), The constant term for fitting (unit: kPa); the coefficients are solved using the least squares method during the fitting process, with a fitting error ≤ 0.1 kPa, ensuring that the curve accurately reflects the elastic characteristics of the intestine (e.g., if the intestine has good elasticity). , Small value, poor elasticity , (High value).

[0049] Furthermore, for the dynamic adjustment of the pressure warning threshold, the adjustment rule is set based on the slope of the compliance curve (i.e., intestinal compliance): when When the intestinal elasticity is good, the influent pressure warning threshold is set to 2.5 kPa; when When the intestinal elasticity is moderate, the warning threshold is set to 2.0 kPa; when When the intestinal elasticity is poor, the warning threshold is set to 1.5 kPa; the outflow pressure warning threshold is adjusted proportionally (the threshold is set to -0.6 kPa when the elasticity is poor and -1.0 kPa when the elasticity is good).

[0050] Based on the above, after the treatment is initiated, the initial water intake phase begins, and the water volume is gradually increased at a fixed flow rate while intestinal pressure data is collected simultaneously. The volume-pressure data is then fused with the input data by the analysis unit, and an intestinal compliance curve is generated through a two-segment nonlinear fitting. The slope of the curve is used to determine the patient's intestinal elasticity level, and the warning threshold of the individualized pressure safety model is dynamically adjusted accordingly. In subsequent treatment, pressure risk assessment is performed based on the adjusted threshold.

[0051] This implementation method achieves individualized adaptation of the pressure warning threshold, avoiding the inapplicability of a uniform threshold to patients with varying intestinal elasticity. Through a precisely fitted compliance curve, patients with poor intestinal elasticity can be identified in advance, reducing the risk of excessive pressure. Simultaneously, by combining real-time collected multi-dimensional data such as temperature and flow rate, the infusion parameters of the colon cleansing solution are dynamically adjusted to ensure the safety and comfort of the colon cleansing process. Furthermore, in some implementations, the system can also establish patient intestinal health records based on long-term data accumulation, providing data support for subsequent diagnosis and treatment, and improving the accuracy and efficiency of intestinal disease diagnosis and treatment.

[0052] Existing automated colon cleansing devices can only passively stop operating after fluid retention actually occurs (such as when a patient experiences abdominal distension or pain). They cannot predict risks based on intestinal physiological characteristics and real-time fluid status, resulting in delayed treatment risk response and easily causing intestinal discomfort or more serious physiological reactions. There is an urgent need for a control logic that can predict the risk of fluid retention in advance and actively intervene.

[0053] Therefore, based on the aforementioned construction of the intestinal compliance model, as a further optional implementation method of this embodiment, the data fusion analysis unit predicts the risk of fluid retention based on the intestinal compliance curve and real-time fluid balance value; When a risk of liquid retention is predicted, the adaptive control unit generates integrated control commands including: reducing the inlet water rate and increasing the outlet negative pressure, and prohibiting the initiation of a new inlet water cycle until the real-time liquid balance value returns to a safe range.

[0054] In practical implementation, the logic for predicting the risk of fluid retention is as follows: the data fusion analysis unit first extracts the key parameters of the intestinal compliance curve, namely the intestinal elasticity coefficient. (Unit: kPa / mL), this coefficient is calculated from the compliance curve generated by fitting, and the formula is as follows: ( This represents the change in intestinal pressure, expressed in kPa. (This represents the change in influent volume, in mL); simultaneously, real-time liquid balance values ​​are acquired. (Unit: mL; calculation method: real-time liquid balance value = total inflow during the cycle - total outflow during the cycle).

[0055] Secondly, the risk prediction model is set as follows: when the following conditions are met... ( (The initial maximum single inflow volume) and When the risk of fluid retention is identified, it is determined that "there is a risk of fluid retention". Among them, "0.6" is the fluid balance warning coefficient and "0.02kPa / mL" is the intestinal low elasticity threshold. This threshold is obtained by statistical analysis of compliance data of 1,000 patients with different intestinal states in clinical practice. In practical applications, it can be adjusted according to the applicable population of the device (such as adults and children). This application embodiment does not limit this.

[0056] Furthermore, the water inlet speed adjustment specifically involves the adaptive control unit reducing the water inlet speed from its current value by 30%-50%, with the specific reduction amount determined based on the liquid retention risk level. If... If so, then reduce by 50%; if If the water inlet speed is reduced by 30%, the water inlet speed will be adjusted by controlling the opening of the proportional valve of the water inlet actuator module. For example, if the current proportional valve opening is 60% (corresponding to a water inlet speed of 150mL / min), after reducing it by 50%, the opening will be adjusted to 30% (corresponding to a water inlet speed of 75mL / min).

[0057] Furthermore, the method for increasing the negative pressure of the outlet water is as follows: the adaptive control unit increases the negative pressure value of the negative pressure pump of the outlet water execution module from the normal working value (-30kPa) to -45kPa~-50kPa. The specific value is dynamically adjusted according to the outlet water pressure feedback to ensure that the outlet water flow rate is increased by 20%-30%. The negative pressure adjustment is achieved by steplessly changing the speed of the negative pressure pump. The negative pressure pump used is the DP-60 model. This model of pump supports stepless speed regulation from 0-3000rpm and the negative pressure adjustment accuracy can reach ±1kPa. It can quickly respond to the negative pressure adjustment requirements. In practical applications, other models of this component (such as DP-80) can also be selected. This application embodiment does not limit this.

[0058] Furthermore, the logic for prohibiting water circulation is as follows: the adaptive control unit sets a "safety range judgment threshold," which is the real-time liquid balance value. ;exist Until the water level drops to this threshold, the system will prevent the "inlet circulation start" command from being triggered, and will continue to extend the drainage time until the current drainage time reaches the normal cycle (e.g., 5 minutes). Meets the standard.

[0059] Based on the above, the data fusion analysis unit links the intestinal compliance curve (reflecting the intestinal capacity to hold fluid) and the real-time fluid balance value (reflecting the degree of imbalance between fluid inflow and outflow) in real time. It identifies fluid retention trends in advance through a preset risk assessment model. Once a risk warning is triggered, the adaptive control unit intervenes simultaneously from two dimensions: "reducing fluid input" and "increasing fluid outflow". It also avoids risk accumulation by prohibiting new water inflow circulation until the fluid balance is restored to a safe state.

[0060] This implementation method enables proactive intervention in the risk of fluid retention. Compared to the reactive response of existing equipment, it addresses the risk earlier, effectively reducing the incidence of abdominal distension and pain in patients. At the same time, through a quantitative risk assessment model and precise parameter adjustment, it avoids the subjective errors of manual intervention, thereby improving the safety and stability of treatment.

[0061] The fluid balance control of existing automatic colon cleansing equipment is mostly open-loop, that is, only fixed water inlet and outlet times are set, and cannot be dynamically adjusted according to the real-time fluid balance status. This often leads to problems such as excessive fluid accumulation (balance value too high) or insufficient cleaning (balance value too low) in actual treatment. There is a lack of a closed-loop precise control mechanism for fluid balance.

[0062] Therefore, based on the aforementioned prediction of liquid retention risk, as a further optional implementation method of this embodiment, the logic for generating comprehensive control commands by the adaptive control unit includes a liquid balance closed-loop control sub-logic, which includes: Set the target range for liquid equilibrium; Compare the real-time liquid balance value with the target range; If the real-time liquid balance value continues to be higher than the upper limit of the target range, an instruction is generated to increase the power of the negative pressure pump in the water output execution module. If the real-time liquid balance value remains below the lower limit of the target range, an instruction will be generated to pause water intake and extend the drainage time.

[0063] In practice, the target range for fluid balance is set as follows: the target range is determined based on the patient's weight, using the following formula: ,in This is the initial maximum single fluid intake (in mL); for example, for a patient weighing 60 kg. The target range is [120mL, 240mL]. This range has been determined through clinical validation. It ensures that there is enough liquid in the intestine to achieve the cleaning effect, while avoiding the risk of excessive liquid. In practical applications, the upper and lower limits of the range can be finely adjusted according to the purpose of the colon cleansing (such as routine cleaning or preoperative preparation). This application does not limit this.

[0064] Secondly, the specific criteria for determining whether a value is consistently higher or lower than the specified value are as follows: the threshold for the determination period is set at 15 seconds, which is the real-time liquid balance value. The corresponding control command will only be triggered if the flow rate is above the upper limit of the target range (such as 240mL in the example above) for 15 consecutive seconds or below the lower limit of the target range (such as 120mL in the example above) for 15 consecutive seconds. The time threshold is set to avoid erroneous operation caused by instantaneous fluctuations of the sensor (such as brief abnormalities in flow rate caused by water flow impact). The judgment time can be adjusted through the human-machine interaction module, and the adjustment range is 10-20 seconds.

[0065] Furthermore, increasing the power of the negative pressure pump specifically involves: when When the pressure remains above the upper limit, the adaptive control unit increases the negative pressure pump power in increments of 5%, maintaining this increase for 5 seconds after each adjustment. If it remains above the upper limit, continue adjusting until... The power of the negative pressure pump will fall back to the target range or reach 90% of its rated power (to avoid pump overload). The power adjustment of the negative pressure pump is achieved by changing its supply voltage. The power adjustment module used is model PM-100. This module supports stepless output of 0-220V voltage and the power adjustment accuracy can reach ±1%. It can stably control the power change of the negative pressure pump. In practical applications, other models of this component can also be selected (such as PM-200). This application embodiment does not limit this.

[0066] In addition, regarding the suspension of water intake and the extension of drainage time, when When the water level remains below the lower limit, the adaptive control unit immediately sends a "pause water intake" command to the water intake execution module (closing the proportional valve and reducing the positive pressure pump speed to idle), while simultaneously extending the current drainage time by 50%; for example, if the normal drainage time is 3 minutes, it will be extended to 4.5 minutes; if the extended time is... Once the water level rises back to the target range, the drainage time returns to normal; if it remains below the lower limit, the drainage time is extended by another 20% (i.e., a total extension of 70%), until... The time required to reach the standard or drain water should be twice the normal time (to avoid excessively low cleaning efficiency).

[0067] Based on the above, the liquid balance closed-loop control sub-logic uses the "target range" as the control benchmark. By continuously monitoring the deviation between the real-time liquid balance value and the range, and combining the "duration" to determine and eliminate interference, targeted measures are taken to "increase drainage power" (to solve the problem of excessive balance) or "suspend water intake + extend drainage" (to solve the problem of excessive balance). This forms a closed-loop control cycle of monitoring-comparison-adjustment-remonitoring to ensure that the liquid balance is always stable within the target range.

[0068] This implementation method achieves dynamic and precise control of fluid balance, which improves the stability of fluid balance values ​​within the target range compared to the fixed timing control of existing equipment. It avoids the intestinal burden caused by excessive fluid and prevents insufficient fluid from affecting the cleaning effect. At the same time, through step-by-step adjustment and time limitation, it avoids drastic fluctuations in control parameters and improves the stability of system operation.

[0069] The safety controls of existing automated colon cleansing equipment are mostly only for single risks (such as excessive pressure) and lack risk level classification. Whether it is an abnormal pressure or an abnormal temperature, the "direct shutdown" strategy is used, which leads to over-intervention in the case of minor abnormalities (affecting treatment efficiency) and insufficient response in the case of serious abnormalities (unable to stop the damage quickly). At the same time, the risk of rapid imbalance of fluid balance is not considered, and the comprehensiveness and flexibility of safety control are insufficient.

[0070] Therefore, as an optional implementation of this embodiment, the intelligent decision-making module further includes a safety decision-making unit, which is configured to: receive the pressure risk assessment results output by the data fusion analysis unit, and receive the colon cleansing fluid temperature data from the data acquisition module; When any of the following conditions are met, the Level 1 security policy is triggered, and the adaptive control unit generates an instruction to immediately stop all execution modules: Condition A: The stress risk assessment result is high risk; Condition B: The temperature of the enemas solution exceeds 41℃ or is below 38℃; When the following conditions are met, the secondary safety strategy is triggered, and the adaptive control unit generates instructions to reduce the water inflow rate and issue a warning: Condition C: The negative offset rate of the real-time liquid balance value exceeds the set threshold.

[0071] In practical implementation, the safety decision unit uses an independent MCU chip (model STM32F103). This chip has a dual-core redundant design, an operating frequency of 72MHz, and can quickly process risk signals and trigger strategies to avoid the failure of safety functions due to the failure of the main control unit. The chip communicates with the data fusion analysis unit via RS485 bus (communication rate 9600bps, transmission delay <10ms) and is connected to the temperature sensor of the data acquisition module via I2C bus to ensure real-time data transmission. In practical applications, other models of MCU chips (such as STM32F407) can also be selected, but this application embodiment does not limit this.

[0072] Secondly, the data fusion analysis unit divides pressure risk into three levels: low risk (inlet pressure ≤ 30 kPa and outlet pressure ≥ -20 kPa), medium risk (30 kPa < inlet pressure ≤ 40 kPa or -30 kPa ≤ outlet pressure < -20 kPa), and high risk (inlet pressure > 40 kPa or outlet pressure < -30 kPa). The high-risk threshold is determined through human intestinal tolerance limit experiments (e.g., the upper limit of short-term intestinal tolerance pressure in adults is 45 kPa) to ensure that intestinal damage can be avoided when the first-level strategy is triggered.

[0073] Temperature data comes from a temperature sensor (model DS18B20) located at the outlet of the water inlet heating unit. This sensor has a measurement range of -55℃ to 125℃, an accuracy of ±0.5℃, and a sampling period of 1 second, enabling it to capture real-time changes in liquid temperature. The safety decision unit receives temperature data in real time and immediately triggers a first-level strategy when the temperature is >41℃ (exceeding human body temperature by 3℃, which can easily cause burns to the intestinal mucosa) or <38℃ (below human body temperature by 1℃, which can easily cause intestinal spasms).

[0074] Negative offset rate The calculation formula (unit: mL / s) is as follows: ,in This represents the liquid balance value (in mL) at the previous sampling time. This represents the liquid balance value (in mL) at the current sampling time. The sampling interval (unit: seconds, which can be a fixed sampling period, such as 1 second) is set to a threshold of 5 mL / s. When the threshold is 5 mL / s, it is determined that the negative offset rate exceeds the limit (meaning that the liquid is discharged rapidly, which may lead to a sudden decrease in the liquid in the intestine, affecting the cleaning effect or causing abnormal intestinal peristalsis).

[0075] Furthermore, regarding the execution of the Level 1 safety strategy: the adaptive control unit sends an "emergency stop" command to all execution modules: the water inlet execution module shuts down the positive pressure pump and proportional valve, and stops the water inlet heating unit; the water outlet execution module shuts down the negative pressure pump; at the same time, an audible and visual alarm is issued through the red warning light (flashing frequency 2Hz) and buzzer (sounding frequency 1kHz) of the human-machine interaction module until the operator presses the "reset" button.

[0076] In addition, regarding the implementation of the secondary safety strategy: the adaptive control unit will reduce the influent rate by 60% (e.g., from 150 mL / min to 60 mL / min), and simultaneously issue an alert via the yellow warning light (always on) and voice announcement ("Rapid fluid balance imbalance, please monitor the patient's condition"); after the alert, the negative offset rate will be monitored every 5 seconds. If it continues for 10 seconds, the water intake rate will resume and the warning will be canceled; if If it lasts for 30 seconds, the security policy will be upgraded to Level 1.

[0077] Based on the above, the safety decision unit independently collects three types of key safety data: pressure risk, liquid temperature, and liquid balance shift rate. Through preset risk level classification (high risk / exceeding limits vs. negative shift rate exceeding limits), it triggers the first-level strategy of "emergency shutdown" (to deal with fatal risks) and the second-level strategy of "deceleration + early warning" (to deal with non-fatal risks), forming a graded and differentiated safety control mechanism. At the same time, independent hardware ensures the reliability of safety functions.

[0078] This implementation method achieves hierarchical and comprehensive safety control. Compared with the single shutdown strategy of existing equipment, it avoids excessive intervention in the event of minor abnormalities, while ensuring rapid loss prevention in the event of serious abnormalities. Furthermore, by monitoring the negative offset rate of fluid balance, it fills the gap in the control of the risk of rapid fluid imbalance in existing equipment, further improving treatment safety and user experience.

[0079] Existing automated colon cleansing equipment typically uses a fixed amount of water per cycle (e.g., 500 mL / cycle) or relies on operator experience for setting, without considering individualized needs due to differences in patient weight (e.g., different intestinal capacities between adults and children, and between obese and thin patients). This can easily lead to problems such as excessive water intake for underweight patients (causing risks) or insufficient water intake for overweight patients (inadequate cleansing), lacking a dynamic adaptation mechanism for water intake based on individual patient parameters.

[0080] Therefore, as an optional implementation of this embodiment, the human-computer interaction module is used to input individual patient parameters, which include at least weight; The data fusion analysis unit is also configured to: calculate the initial upper limit of single-time water intake based on the body weight and the preset mapping relationship between body weight and single-time safe water intake; and dynamically adjust the upper limit of single-time water intake based on real-time fluid balance values ​​and pressure risk assessment results during treatment.

[0081] In specific implementation, the human-computer interaction module adopts a 10.1-inch touch screen (model TFT-LCD-101) with a resolution of 1920×1080, supports multi-touch, and has a "Patient Information Input" area. "Weight" is a required field with an input range of 5kg to 150kg (covering children to adults) and an input accuracy of 0.1kg. It also supports automatic import of weight data by scanning the patient's medical record barcode with a barcode scanner (model LS2200) to avoid manual input errors. In practical applications, other models of touch screens (such as TFT-LCD-121) can also be selected, but this application embodiment does not limit this.

[0082] Secondly, the mapping relationship between body weight and single safe water intake volume adopts a linear mapping model, the formula is as follows: ,in, This represents the initial maximum single influent volume (in mL). Patient weight (in kg); This model, derived from clinical data fitting, shows that for every 1 kg increase in weight, the safe intestinal capacity increases by 10 mL, with a baseline capacity of 100 mL (e.g., for a 5 kg child). 60kg adult The mapping relationship can be updated through the system backend to adapt to models derived from different clinical studies, and this application does not limit this.

[0083] In addition, after each treatment cycle (water intake + drainage constitutes one cycle, with a typical cycle duration of 5-8 minutes) is completed, the data fusion analysis unit determines whether to make corrections based on the following two indicators. : ① Real-time liquid balance value index: If the maximum liquid balance value within the period (This indicates that the inflow rate is close to the upper limit but has not been fully discharged, and needs to be reduced.) ); if the maximum liquid equilibrium value within the period (This indicates that the inflow rate is far below the upper limit and is being discharged quickly; the flow rate can be increased.) ).

[0084] ② Stress risk assessment index: Real-time pressure values ​​collected by intestinal pressure sensors Exceeding the safety threshold If the stress level is 80% or higher, and the duration exceeds 30 seconds during the treatment cycle, a stress risk is identified, and the treatment should be adjusted downwards. To reduce the burden on the intestines; if the real-time pressure value during the entire treatment period... Always below the safety threshold If it is 50%, then it can be appropriately increased. To optimize treatment efficiency while ensuring safety.

[0085] Based on the above, the system collects multi-dimensional data such as intestinal pressure, fluid temperature, and flow rate in real time using multiple sensors, and uses data fusion algorithms to normalize and perform deep correlation analysis on these heterogeneous data. The system dynamically compares the collected pressure data with preset safety thresholds, and combines the changing trends of temperature and flow rate data to construct a real-time model of the intestinal state, thereby precisely controlling the flow rate, temperature, and perfusion pressure of the enema solution.

[0086] Using this implementation method, the collaborative analysis of multidimensional data can promptly detect abnormal fluctuations in intestinal pressure, provide early warnings of risks such as intestinal perforation, and avoid misjudgments caused by the limitations of single data monitoring. By precisely controlling the parameters of the enema solution, the enema process can be ensured to be comfortable and efficient, reducing patient discomfort and improving intestinal cleansing effects, while providing more accurate basic data support for subsequent diagnosis and treatment.

[0087] Even if existing automated colon cleansing devices can initially determine the upper limit of water intake based on weight, they lack a dynamic optimization mechanism based on the actual effects of the treatment process (such as pressure stability and fluid balance). This results in the upper limit of water intake being either consistently too high (posing a continuous risk) or consistently too low (insufficient cleaning efficiency). They cannot achieve precise adaptation based on the patient's real-time status during treatment, and a quantitative scoring and correction logic is urgently needed.

[0088] Therefore, based on the aforementioned dynamic correction, as a further optional implementation method of this embodiment, the data fusion analysis unit performs the following steps when dynamically correcting the upper limit of a single water inflow: Obtain scores for pressure stability and fluid balance achievement during the current treatment cycle; If the score is lower than the adaptability threshold, the upper limit of the single water intake in the next cycle will be reduced by a preset step size. If the score is higher than the optimization threshold for several consecutive cycles, the upper limit of the single water intake will be increased by a preset step size until the theoretical maximum value calculated based on body weight is reached.

[0089] In practical implementation, the pressure stability score (denoted as...) (100 points total) Calculated based on the fluctuation of inlet pressure within the current cycle, the formula is: ,in The standard deviation of the inlet pressure during the cycle (in kPa). This represents the average inlet pressure (in kPa) over a given period; for example, within a certain period... , ,but The score is calculated based on clinical data, ensuring that the smaller the stress fluctuations, the higher the score, thus objectively reflecting stress stability.

[0090] Secondly, the fluid balance compliance score (denoted as...) (100 points total) Calculated based on the percentage of the duration of the real-time liquid balance value within the target interval in the current period, using the following formula: ,in Within the period Total duration within the target interval (in seconds). The total duration of the cycle (in seconds); for example, a total cycle duration of 300 seconds. s, then Points; if an event exceeds the safe range within the period (e.g.) If the score exceeds 1 second, 2 points will be deducted, until all points are deducted.

[0091] Regarding the setting of the comprehensive score and threshold, the data fusion analysis unit takes... and The average value is used as the comprehensive score for the current period ( The adaptability threshold is set to 60 points, and the optimization threshold is set to 85 points. These thresholds are derived from statistical data of 1,000 clinical treatment cases. A score below 60 points indicates that the current upper limit of water intake does not match the patient's condition, while a score above 85 points indicates that there is room for optimization of the current upper limit of water intake. In practical applications, these thresholds can be fine-tuned according to the equipment usage scenario (such as outpatient or inpatient settings). This application embodiment does not limit these adjustments.

[0092] Furthermore, regarding the preset step size and cycle number settings, the adjustment step size for the upper limit of the single influent volume is set to 50mL, that is, when adjusting downwards... When adjusted upwards Multiple consecutive cycles can be set to 3 cycles, meaning 3 consecutive cycles are required. The adjustment is triggered by the step size; the setting of the step size and the number of cycles ensures both the safety of the adjustment (avoiding excessive adjustment in a single instance) and the timeliness of the optimization (initial adaptation can be completed within 3 cycles).

[0093] Furthermore, regarding the theoretical maximum limit, the theoretical maximum value calculated based on body weight is... The calculation results, during the upward adjustment process Once the theoretical maximum value is reached, the adjustment should be stopped to avoid exceeding the safe upper limit based on body weight; for example, the theoretical maximum value for a patient weighing 60kg is 700mL. The initial value was 650 mL, which was increased once to 700 mL. No further adjustments were made even if the score remained within the acceptable range.

[0094] Based on the above, the data fusion analysis unit converts pressure stability and liquid balance compliance into calculable scores through quantitative formulas. The comprehensive score is then used as the basis for judgment. When the score is low, the upper limit of the water inflow is lowered to reduce risk, and when the score is consistently high, it is raised to improve efficiency. At the same time, the step size and theoretical maximum value limit are used to ensure the safety of the adjustment, forming a closed-loop optimization mechanism of scoring-judgment-correction.

[0095] This implementation method achieves dynamic quantitative optimization of the upper limit of single water intake, which improves the patient's pressure stability score and fluid balance achievement score during treatment compared to a fixed upper limit. It can quickly adapt to the patient's real-time intestinal status, avoid the subjectivity of manual adjustment, and balance safety and cleaning efficiency.

[0096] Secondly, this embodiment provides a method (hereinafter referred to as "the method") applied to the automated colon cleansing system based on multidimensional data fusion analysis as described above. The method is executed by the intelligent decision-making module and includes the following steps: Multidimensional data acquisition steps: Real-time data streams of the colon cleansing process are collected synchronously through the data acquisition module. The real-time data streams include at least the inlet water pressure, outlet water pressure, inlet water flow rate, and outlet water flow rate. Data fusion and analysis steps: The data fusion and analysis unit receives and processes the real-time data stream, and performs the following operations: S11 - Liquid Balance Calculation: Calculates real-time liquid balance values ​​based on influent and effluent flow rates within a cycle; S12 - Pressure Risk Assessment: Calls a preset individualized pressure safety model to analyze the inlet and outlet pressures and generate pressure risk assessment results; Adaptive closed-loop control steps: The adaptive control unit performs the following operations based on the real-time liquid balance value and pressure risk assessment results: S21 - Control Command Generation: Based on the fusion judgment of real-time liquid balance value and pressure risk assessment results, a comprehensive control command is generated; S22 - Execution and Adjustment: Sends integrated control commands to the inlet and outlet execution modules to dynamically adjust the inlet and outlet speeds and determine the start and stop times for the next inlet cycle.

[0097] It should be noted that this method corresponds to the aforementioned automated colon cleansing device system based on multidimensional data fusion analysis. Therefore, the parts of this method that are not specifically described (including but not limited to specific technical means and effects) can be referred to the relevant descriptions in the aforementioned automated colon cleansing device system based on multidimensional data fusion analysis, and will not be repeated here.

[0098] In the embodiments provided by this invention, it should be understood that the embodiments described herein can be implemented in hardware, software, firmware, middleware, code, or any suitable combination thereof. For hardware implementation, the processor can be implemented in one or more of the following: application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field-programmable gate arrays (FPGAs), processors, controllers, microcontrollers, microprocessors, other electronic units designed to implement the functions described herein, or combinations thereof. For software implementation, some or all of the processes of the embodiments can be performed by a computer program instructing the associated hardware. During implementation, the program can be stored in a computer-readable storage medium or transmitted as one or more instructions or code on a computer-readable storage medium. Computer-readable storage media include computer storage media and communication media, wherein communication media include any medium that facilitates the transmission of a computer program from one place to another. Storage media can be any available medium accessible to a computer. Computer-readable storage media can include, but are not limited to, RAM, ROM, EEPROM, CD-ROM or other optical disk storage, magnetic disk storage media or other magnetic storage devices, or any other medium capable of carrying or storing desired program code having the form of instructions or data structures and accessible to a computer.

[0099] Finally, it should be noted that the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments or make equivalent substitutions for some of the technical features. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. An automatic colon cleansing system based on multidimensional data fusion analysis, comprising a water inlet execution module, a water outlet execution module, a data acquisition module, and a human-computer interaction module, characterized in that, Also includes: The intelligent decision-making module is communicatively connected to the water inlet execution module, the water outlet execution module, the data acquisition module, and the human-machine interaction module, respectively; wherein, the intelligent decision-making module includes: The data fusion and analysis unit is configured to: receive a real-time data stream from the data acquisition module, the real-time data stream including at least inlet water pressure, outlet water pressure, inlet water flow rate, and outlet water flow rate; calculate a real-time liquid balance value based on the inlet water flow rate and the outlet water flow rate; and perform a pressure risk assessment based on the inlet water pressure, the outlet water pressure, and a preset individualized pressure safety model. The adaptive control unit is configured to generate a comprehensive control command based on the real-time liquid balance value output by the data fusion analysis unit and the pressure risk assessment result; the comprehensive control command is used to dynamically adjust the water inlet speed of the water inlet execution module and the water outlet speed of the water outlet execution module, and to determine the start and stop timing of the next water inlet cycle. The intelligent decision-making module, through the coordinated operation of the data fusion analysis unit and the adaptive control unit, constitutes a fully closed-loop adaptive control of the colon cleansing process.

2. The automated colon cleansing system based on multidimensional data fusion analysis according to claim 1, characterized in that, The data fusion and analysis unit is also configured to: construct a gut compliance model, wherein the steps for constructing the gut compliance model include: During the initial water intake phase, data on changes in intestinal pressure were recorded under different water intake volumes. Based on the correlation between the changes in intestinal pressure and the volume of water intake, an intestinal compliance curve reflecting the current intestinal elasticity characteristics of the patient is fitted and generated. The pressure warning threshold of the individualized stress safety model is dynamically adjusted based on the intestinal compliance curve.

3. The automated colon cleansing system based on multidimensional data fusion analysis according to claim 2, characterized in that, The data fusion analysis unit predicts the risk of fluid retention based on the intestinal compliance curve and the real-time fluid balance value; When a risk of liquid retention is predicted, the comprehensive control commands generated by the adaptive control unit include: reducing the inlet water rate and increasing the outlet negative pressure, and prohibiting the initiation of a new inlet water cycle until the real-time liquid balance value is restored to a safe range.

4. The automated colon cleansing system based on multidimensional data fusion analysis according to claim 3, characterized in that, The logic for generating integrated control commands by the adaptive control unit includes a liquid balance closed-loop control sub-logic, which includes: Set the target range for liquid equilibrium; Compare the real-time liquid balance value with the target range; If the real-time liquid balance value continues to be higher than the upper limit of the target range, an instruction is generated to increase the negative pressure pump power of the water outlet execution module. If the real-time liquid balance value remains below the lower limit of the target range, an instruction is generated to pause water intake and extend the drainage time.

5. The automated colon cleansing system based on multidimensional data fusion analysis according to claim 1, characterized in that, The intelligent decision-making module also includes a safety decision-making unit, which is configured to: receive the pressure risk assessment result output by the data fusion analysis unit, and receive the colon cleansing fluid temperature data from the data acquisition module; The first-level security policy is triggered when any of the following conditions are met, and the adaptive control unit generates an instruction to immediately stop all execution modules: Condition A: The stress risk assessment result is high risk; Condition B: The temperature of the enemas is above 41°C or below 38°C; When the following conditions are met, the secondary safety strategy is triggered, and the adaptive control unit generates an instruction to reduce the water inflow rate and issue a warning: Condition C: The negative offset rate of the real-time liquid balance value exceeds a set threshold.

6. The automated colon cleansing system based on multidimensional data fusion analysis according to claim 1, characterized in that, The human-computer interaction module is used to input individual patient parameters, which include at least weight. The data fusion and analysis unit is further configured to: calculate the initial upper limit of single water intake based on the weight and a preset mapping relationship between weight and single safe water intake; During the treatment process, the upper limit of the single water intake is dynamically adjusted based on the real-time fluid balance value and the pressure risk assessment results.

7. The automated colon cleansing system based on multidimensional data fusion analysis according to claim 6, characterized in that, When dynamically correcting the upper limit of a single water inflow, the data fusion and analysis unit performs the following steps: Obtain scores for pressure stability and fluid balance achievement during the current treatment cycle; If the score is lower than the adaptability threshold, the upper limit of the single water intake in the next cycle will be reduced by a preset step size. If the score is higher than the optimization threshold for several consecutive cycles, the upper limit of the single water intake will be increased by a preset step size until the theoretical maximum value calculated based on body weight is reached.

8. The automated colon cleansing system based on multidimensional data fusion analysis according to claim 1, characterized in that, The water intake execution module includes a positive pressure pump, a proportional valve, and a water intake heating unit. The adaptive control unit adjusts the opening of the proportional valve and the rotation speed of the positive pressure pump to coordinately control the water intake speed and pressure, and maintains the liquid temperature at a set value by controlling the working power of the water intake heating unit. The water discharge execution module includes a negative pressure pump and a waste liquid temporary storage container. The speed of the negative pressure pump is steplessly adjusted by the adaptive control unit according to the real-time liquid balance value and the water discharge pressure.

9. The automated colon cleansing system based on multidimensional data fusion analysis according to claim 1, characterized in that, The data acquisition module includes: The first pressure sensor and the second pressure sensor are respectively installed on the water inlet passage and the water outlet passage, and are used to collect the water inlet pressure and the water outlet pressure. The first flow meter and the second flow meter are respectively installed on the inlet passage and the outlet passage to collect the inlet flow rate and the outlet flow rate; A temperature sensor is installed at the outlet of the water inlet heating unit to collect the temperature of the enemas. The data fusion and analysis unit synchronously acquires data from each sensor at a fixed sampling period and aligns the timestamps to form the real-time data stream.

10. A method applied to an automated colon cleansing system based on multidimensional data fusion analysis as described in any one of claims 1 to 9, characterized in that, This method is executed by the intelligent decision-making module and includes the following steps: Multidimensional data acquisition steps: Real-time data streams of the colon cleansing process are synchronously acquired through the data acquisition module. The real-time data streams include at least inlet water pressure, outlet water pressure, inlet water flow rate, and outlet water flow rate. Data fusion and analysis steps: The data fusion and analysis unit receives and processes the real-time data stream, and performs the following operations: S11 - Liquid Balance Calculation: Calculate the real-time liquid balance value based on the influent flow rate and the effluent flow rate within the cycle; S12 - Pressure Risk Assessment: Invoke the preset individualized pressure safety model to analyze the inlet pressure and the outlet pressure, and generate pressure risk assessment results; Adaptive closed-loop control steps: The adaptive control unit performs the following operations based on the real-time liquid balance value and the pressure risk assessment result: S21 - Control Command Generation: Based on the fusion judgment of the real-time liquid balance value and the pressure risk assessment result, a comprehensive control command is generated; S22 - Execution and Adjustment: The integrated control command is sent to the water inlet execution module and the water outlet execution module to dynamically adjust the water inlet speed and the water outlet speed, and to determine the start and stop time of the next water inlet cycle.

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