Implantable infusion port leakage monitoring system and method for medical oncology

Abstract

The invention discloses a medical oncology implantable infusion port leakage monitoring system and method, and relates to the technical field of infusion leakage detection. The multi-parameter sensor module is used for monitoring pressure fluctuation in an infusion port, sensing temperature change of surrounding tissues, detecting abnormal leakage conditions of medicine components and obtaining multi-parameter sensor data; the flexible electronic circuit module is used for processing multi-parameter sensor data in real time; the data analysis and early warning module is used for performing real-time analysis on the processed multi-parameter sensor data and performing graded early warning; and the wireless communication module is used for transmitting the data of the multi-parameter sensor to an external terminal in real time by adopting a wireless communication technology. The invention relates to data acquisition, signal processing, feature extraction and fusion, leakage threshold judgment and response and feedback of an alarm mechanism, the accuracy of sensor data is ensured by applying a multi-modal fusion algorithm, and the safety and medical response efficiency of a patient are improved through a graded early warning mechanism.

Description

Technical Field

[0001] The present invention belongs to the technical field of infusion leakage monitoring, and in particular relates to a leakage monitoring system and method for an implantable infusion port in oncology. Background Art

[0002] During cancer treatment, long-term infusion of chemotherapy and other drugs is a common treatment method. In order to avoid frequent needle sticks and reduce patient discomfort, an implantable port is usually used. This device can be implanted in the patient's body for a long time to provide a stable drug delivery channel. However, the implantable port may leak during long-term use, especially when there is a problem with the connection between the catheter and the blood vessel. These leaks can cause drugs or nutrients to leak into the body cavity, which may cause local tissue damage, infection, pain and other problems, and in severe cases may endanger the patient's health.

[0003] At present, the clinical leakage monitoring methods for implantable infusion ports are relatively simple, and leakage cannot be detected in time, resulting in some patients not being treated in time, which increases the risk of treatment. The main focus is on: (1) Real-time and accuracy of leakage detection: Existing technologies often rely on manual observation or regular inspection methods, which cannot achieve real-time monitoring of infusion port leakage and pose a risk of missed diagnosis. (2) Invasiveness and comfort of monitoring methods: Some existing leakage detection methods may require frequent intervention of external equipment or additional in vivo monitoring, which may have an adverse effect on the comfort and safety of patients. (3) Difficulty in detecting leakage in the early stages: Leakage is often not obvious in the early stages, and traditional inspection methods are difficult to detect leakage in the early stages, missing the best treatment opportunity. (4) Monitoring of complex fluids: There are many types of chemotherapy fluids and nutrient solutions, and their reactions in the body are complex. Existing sensor systems often have difficulty in meeting the detection needs of different fluid leakage.

[0004] Therefore, developing a technology that can monitor implantable infusion port leakage in real time is of great clinical significance. Summary of the invention

[0005] The purpose of the present invention is to provide a leakage monitoring system and method for an implantable infusion port in oncology, which can be achieved through the following technical solutions: In a first aspect, an embodiment of the present application provides a leakage monitoring system for an implantable infusion port in oncology, comprising: Multi-parameter sensor module: used to monitor pressure fluctuations in the implantable infusion port, sense changes in surrounding tissue temperature, and detect abnormal leakage of specific chemotherapy drug components, thereby obtaining multi-parameter sensor data; Flexible electronic circuit module: used for real-time processing of the multi-parameter sensor data; Data analysis and early warning module: used to analyze the processed multi-parameter sensor data in real time and issue graded early warnings based on the analysis results; Wireless communication module: used to transmit the multi-parameter sensor data to an external terminal in real time using wireless communication technology.

[0006] Preferably, the multi-parameter sensor module comprises a pressure sensor unit, a chemical sensor unit and a temperature sensor unit; The pressure sensor unit is used to monitor the pressure changes inside the implantable infusion port in real time and distinguish between infusion operations and leakage events through pressure fluctuation patterns; The chemical sensor unit is used to detect key indicators of chemotherapy drug leakage, including concentration of specific drug components and pH changes, and to distinguish drug leakage from body fluid leakage; The temperature sensor unit is used to sense the temperature abnormality of the tissue around the implantable infusion port and combine the pressure data / chemical data to eliminate the interference of non-leakage heating.

[0007] Preferably, the multi-parameter sensor module further comprises a flow sensor unit and a bioimpedance sensor unit; The flow sensor unit is used to monitor the liquid flow rate in the infusion pipeline, and triggers an early warning signal if the liquid flow rate increases or decreases abnormally; it is also linked with the pressure sensor to distinguish leakage events from mechanical failures; The bioimpedance sensor unit is used to monitor the impedance changes of the tissues around the implantable infusion port and evaluate the degree of damage to the local tissues caused by leakage.

[0008] Preferably, the flexible electronic circuit module includes a data preprocessing unit, an analog-to-digital conversion unit and an embedded processing unit; The data preprocessing unit is used to denoise, filter and amplify the original signal in the multi-parameter sensor data to generate an analog signal, specifically: processing the signal-to-noise ratio through a low-noise amplifier and an adaptive filtering circuit, and adjusting the amplitude of the original signal to adapt to the input range of the analog-to-digital converter; The analog-to-digital conversion unit is used to convert the conditioned analog signal into a digital signal, specifically: time-division multiplexing sampling of the original signal at a high rate; converting the analog quantity into a digital signal through quantization and encoding; The embedded processing unit runs a leakage detection algorithm based on the digital signal to perform multi-sensor data fusion, dynamic threshold judgment and early warning decision-making.

[0009] Preferably, multi-sensor data fusion is performed in the embedded processing unit, specifically: Feature extraction: extracting key features for distinguishing a leakage state from a normal state from the digital signal; Multimodal fusion: primary fusion based on rules and primary logic judgment; secondary fusion based on machine learning models and secondary model judgment; if it is not determined as a leakage event in the primary logic judgment, it will enter the secondary model judgment, specifically: In the first-level logic judgment, if the conditions of pressure drop, pH deviation and local temperature rise are met at the same time, it is judged as a leakage event, otherwise it enters the second-level model judgment; Among them, the key features include pressure change slope, pressure fluctuation variance, pH value offset, specific ion concentration gradient, local temperature rise rate, temperature transient peak and multi-sensor temperature difference.

[0010] Preferably, in the multimodal fusion, secondary fusion is performed based on a machine learning model, including: Feature-level fusion: concatenate the feature vectors of the key features into a unified input; Model selection: Random forest is used for embedded deployment to support the importance assessment of the key features; lightweight neural network is also used to process the time series features in the key features; Decision-level fusion: Each sensor makes an independent judgment and then votes.

[0011] Preferably, the dynamic threshold determination is performed in the embedded processing unit through a dynamic adaptive mechanism, specifically: Individualized threshold adjustment: Dynamically update alarm thresholds based on the patient's baseline data, including resting body temperature and daily stress fluctuation range; Time series context analysis: Combine historical data to determine the severity of the current event and perform early warning based on the judgment results.

[0012] Preferably, the data analysis and warning module includes a real-time analysis unit, a hierarchical warning unit and an emergency response linkage unit; The real-time analysis unit is used to calculate the leakage risk index in real time based on the fusion result of the multi-sensor data to perform dynamic risk assessment; it also analyzes the change trend of the multi-sensor data over time through time series pattern recognition to distinguish acute leakage from chronic leakage; it is also used to exclude non-leakage events by filtering interference scenes; The graded warning unit is used to set the warning level and trigger conditions according to the severity of the leakage event, and associate different warning levels with corresponding treatment measures; the warning levels include level one warning, level two warning and level three warning; The emergency response linkage unit is used to perform equipment linkage, information push and emergency processing according to the warning level.

[0013] Preferably, the oncology implantable infusion port leakage monitoring system further comprises a self-powered module for generating electricity using glucose or blood flow in the body, and combined with a micro lithium battery to extend the battery life of the monitoring device; The self-powered module includes a bioenergy collection unit, an energy storage unit, a power management unit and an energy status linkage unit; The bioenergy collection unit utilizes enzyme-catalyzed glucose oxidation reaction and oxygen reduction reaction to generate electrical energy; it also utilizes blood flow in blood vessels to drive micro-turbines or piezoelectric materials to generate electricity; The energy storage unit is used to store redundant power of the bioenergy collection unit for use during peak loads; The power management unit is used to dynamically assign energy source priorities and switch power supply modes and adjust power supply voltage according to load requirements; The energy status linkage unit is used to cooperate with the hierarchical warning mechanism of the hierarchical warning unit to trigger corresponding alarms when energy is insufficient and optimize power consumption to extend battery life.

[0014] In a second aspect, the present application provides a method for monitoring leakage of an implantable infusion port in oncology, comprising the following steps: Monitor pressure fluctuations in implanted infusion ports, sense temperature changes in surrounding tissues, and detect abnormal leakage of specific chemotherapy drug components to obtain multi-parameter sensor data; Processing the multi-parameter sensor data in real time; Conduct real-time analysis on the processed multi-parameter sensor data and issue graded warnings based on the analysis results; Using wireless communication technology to transmit the multi-parameter sensor data to an external terminal in real time; It uses glucose or blood flow in the body to generate electricity and combines it with a micro lithium battery to extend the battery life of the monitoring device.

[0015] The beneficial effects of the present invention are as follows: the present invention relates to data acquisition, signal processing, feature extraction and fusion, leakage threshold judgment and alarm mechanism response and feedback, ensures the accuracy of sensor data by applying a multimodal fusion algorithm, ensures the timeliness of safety prompts by a graded early warning mechanism, and adopts a modular design to be compatible with the existing infusion port structure, thereby reducing equipment costs. It can be seen that the present application achieves the accuracy and timeliness of implantable infusion port leakage monitoring through the above content, thereby improving patient safety and medical response efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] For better understanding and implementation, the technical solution of the present application is described in detail below with reference to the accompanying drawings.

[0017] Figure 1A schematic diagram of a leakage monitoring system for an implantable infusion port for oncology provided in an embodiment of the present application; Figure 2 A schematic diagram of the structure of a multi-parameter sensor module provided in an embodiment of the present application; Figure 3 A schematic diagram of the structure of a flexible electronic circuit module provided in an embodiment of the present application; Figure 4 A flowchart of the steps of a method for monitoring leakage of an implantable infusion port in oncology provided in an embodiment of the present application. DETAILED DESCRIPTION

[0018] In order to further explain the technical means and effects taken by the present invention to achieve the predetermined invention purpose, exemplary embodiments will be described in detail here, and examples thereof are shown in the accompanying drawings. When the following description refers to the drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The implementations described in the following exemplary embodiments do not represent all implementations consistent with the present application. Instead, they are only examples of methods and systems consistent with some aspects of the present application as detailed in the attached claims.

[0019] The terms used in this application are only for the purpose of describing specific embodiments and are not intended to limit this application. The singular forms of "a", "said" and "the" used in this application and the appended claims are also intended to include plural forms unless the context clearly indicates other meanings. It should also be understood that the term "and / or" used in this article refers to any or all possible combinations of one or more associated listed items.

[0020] The specific implementation methods, features and effects of the present invention are described in detail below in conjunction with the accompanying drawings and preferred embodiments.

[0021] Example 1 See also Figure 1 The present application embodiment provides a leakage monitoring system for an implantable infusion port in oncology, comprising: Multi-parameter sensor module: used to monitor pressure fluctuations in the implantable infusion port, sense changes in surrounding tissue temperature, and detect abnormal leakage of specific chemotherapy drug components, thereby obtaining multi-parameter sensor data; Flexible electronic circuit module: used for packaging with biocompatible materials and integrating low-power chips to process the multi-parameter sensor data in real time; Data analysis and early warning module: used to analyze the processed multi-parameter sensor data in real time and issue graded early warnings based on the analysis results; Wireless communication module: used to transmit the multi-parameter sensor data to an external terminal in real time using wireless communication technology.

[0022] Specifically, since implantable infusion ports are usually used for patients undergoing long-term chemotherapy, they are buried under the patient's skin and connected to the central vein to facilitate drug infusion. Leakage refers to the leakage of drugs or liquids into surrounding tissues, which may lead to infection, tissue damage or other complications. Therefore, it is particularly important to monitor the leakage of implantable infusion ports. However, the existing monitoring methods are relatively single, the monitoring is not sensitive enough and the data is not accurate enough, which will lead to inaccurate results obtained from data analysis, thereby affecting the judgment of medical staff. Therefore, it is necessary to monitor the leakage of implantable infusion ports in an all-round way, including but not limited to monitoring the pressure fluctuations in the implantable infusion port, sensing the temperature changes of the surrounding tissues, and detecting the abnormal leakage of specific chemotherapy drug components. The sensor data obtained is then processed by a flexible electronic circuit module, and the analysis results after data analysis are graded and warned. Data is also exchanged with external terminals through wireless communication technology, and power generation is achieved in the body through a self-powered module to maintain the operation of the monitoring system.

[0023] This application involves data acquisition, signal processing, feature extraction and fusion, leakage threshold judgment and alarm mechanism response and feedback, and ensures the accuracy of sensor data by applying multimodal fusion algorithms, ensures the timeliness of safety prompts by using graded early warning mechanisms, and adopts modular design to be compatible with existing infusion port structures, thereby reducing equipment costs. It can be seen that this application achieves the accuracy and timeliness of implantable infusion port leakage monitoring through the above content, thereby improving patient safety and medical response efficiency.

[0024] like Figure 2 As shown, in one embodiment provided in the present application, the multi-parameter sensor module includes a pressure sensor unit, a chemical sensor unit and a temperature sensor unit; The pressure sensor unit is used to monitor the pressure changes inside the implantable infusion port in real time and distinguish between infusion operations and leakage events through pressure fluctuation patterns; The chemical sensor unit is used to detect key indicators of chemotherapy drug leakage, including concentration of specific drug components and pH changes, and to distinguish drug leakage from body fluid leakage; The temperature sensor unit is used to sense the temperature abnormality of the tissue around the implantable infusion port and combine the pressure data / chemical data to eliminate the interference of non-leakage heating.

[0025] Specifically, the present application uses a pressure sensor unit to monitor the internal pressure changes of the infusion port in real time (the pressure is stable during normal infusion and the pressure drops sharply during leakage); the pressure fluctuation pattern (such as slope change) is used to distinguish between infusion operations (normal pressure fluctuations) and leakage events. The specific technical implementation is as follows: Micro piezoresistive sensor: implantable design, the detection range covers the physiological pressure of the human body (0~300 mmHg); dynamic baseline calibration: automatically adjust the reference pressure threshold according to the patient's position changes (such as lying down / standing). The chemical sensor unit is also used to detect key indicators of chemotherapy drug leakage (such as specific drug component concentration, pH value changes), and distinguish leaked drugs from body fluids (such as blood, tissue fluid) to reduce false alarms. The specific technical implementation is as follows: Electrochemical sensor array: pH sensor: monitors local pH changes caused by drug leakage (chemotherapeutic drugs are mostly alkaline or acidic); ion-selective electrode: detects specific chemotherapy drugs (such as platinum ions of cisplatin and fluoride ions of fluorouracil).

[0026] Molecularly imprinted polymer (MIP) sensor: customized recognition of specific drug molecules (such as paclitaxel, doxorubicin). The temperature sensor is also used to sense abnormal temperature increases in the tissues around the infusion port (drug leakage may trigger local inflammatory reactions), and combined with pressure / chemical data, it eliminates interference from non-leakage fever (such as infection). The specific technical implementation is as follows: Miniature thermocouple or thermistor: accuracy ±0.1°C, response time <1 second.

[0027] Multi-location distributed temperature measurement: Deploy multiple sensors on the surface of the infusion port to locate leakage hotspots.

[0028] In one embodiment provided in the present application, the multi-parameter sensor module further includes a flow sensor unit and a bioimpedance sensor unit; The flow sensor unit is used to monitor the liquid flow rate in the infusion pipeline, and triggers an early warning signal if the liquid flow rate increases or decreases abnormally; it is also linked with the pressure sensor to distinguish leakage events from mechanical failures; The bioimpedance sensor unit is used to monitor the impedance changes of the tissues around the implantable infusion port and evaluate the degree of damage to the local tissues caused by leakage.

[0029] Specifically, the present application monitors the liquid flow rate in the infusion pipeline through a flow sensor unit, triggers an early warning when the flow rate increases abnormally (such as a pipeline rupture) or decreases (such as a blockage); and works in conjunction with a pressure sensor to distinguish between leakage events and mechanical failures (such as a pump blockage). The specific technical implementation is as follows: Micro ultrasonic Doppler flowmeter: non-invasive measurement, avoiding contact with liquid medicine.

[0030] Thermal flow sensor: detects changes in fluid heat conduction through a heating element.

[0031] The present application also uses a bioimpedance sensor unit to monitor the impedance changes of the tissue around the infusion port (leakage causes changes in tissue fluid composition or edema) and evaluates the degree of damage to local tissue caused by leakage. The specific technical implementation is: multi-frequency bioimpedance analysis (BIA): through 10kHz~1MHz frequency scanning, distinguish the changes in intracellular and extracellular fluid.

[0032] In summary, the present application ensures the accuracy of leakage monitoring through the synergy and spatiotemporal correlation of the above-mentioned multiple sensors, and significantly reduces the false positive rate through the three-level verification logic of pressure, chemical and temperature sensors (such as pressure drop + pH abnormality + local temperature rise = confirmed leakage). The spatial distribution of sensors (such as temperature sensor array) is used to locate the leakage point, and the leakage development stage is judged in combination with time series data (such as pressure drop earlier than temperature rise). Therefore, through the collaborative work of multiple sensors, the above-mentioned multi-parameter sensor module can achieve high-precision and low-latency detection of leakage events, while reducing interference with patients' daily lives.

[0033] like Figure 3 As shown, in one embodiment provided in the present application, the flexible electronic circuit module includes a data preprocessing unit, an analog-to-digital conversion unit, and an embedded processing unit; The data preprocessing unit is used to denoise, filter and amplify the original signal in the multi-parameter sensor data to generate an analog signal, specifically: processing the signal-to-noise ratio through a low-noise amplifier and an adaptive filtering circuit, and adjusting the amplitude of the original signal to adapt to the input range of the analog-to-digital converter; The analog-to-digital conversion unit is used to convert the conditioned analog signal into a digital signal, specifically: time-division multiplexing sampling of the original signal at a high rate; converting the analog quantity into a digital signal through quantization and encoding; The embedded processing unit runs a leakage detection algorithm based on the digital signal to perform multi-sensor data fusion, dynamic threshold judgment and early warning decision-making.

[0034] Specifically, in this embodiment, the data of the multi-parameter sensor is first conditioned and amplified (denoising, filtering and amplification) in the data preprocessing unit in the flexible electronic circuit module, then converted into a digital signal by the analog-to-digital conversion unit, and finally processed by the embedded processing unit (such as data fusion, algorithm judgment). The entire data processing process is mainly completed in the flexible electronic circuit module to ensure fast response and low power consumption. In addition, through the above design, the flexible electronic circuit module is not only the "brain" of data processing, but also undertakes the full-process optimization task of the signal link to ensure the reliability and efficiency of the system in the implant environment.

[0035] In an embodiment provided in the present application, multi-sensor data fusion is performed in the embedded processing unit, specifically: Feature extraction: extracting key features for distinguishing a leakage state from a normal state from the digital signal; Multimodal fusion: primary fusion based on rules and primary logic judgment; secondary fusion based on machine learning models and secondary model judgment; if it is not determined as a leakage event in the primary logic judgment, it will enter the secondary model judgment, specifically: In the first-level logic judgment, if the conditions of pressure drop, pH deviation and local temperature rise are met at the same time, it is judged as a leakage event, otherwise it enters the second-level model judgment; Among them, the key features include pressure change slope, pressure fluctuation variance, pH value offset, specific ion concentration gradient, local temperature rise rate, temperature transient peak and multi-sensor temperature difference.

[0036] In an embodiment provided in the present application, in the multimodal fusion, secondary fusion is performed based on a machine learning model, including: Feature-level fusion: concatenate the feature vectors of the key features into a unified input; Model selection: Random forest is used for embedded deployment to support the importance assessment of the key features; lightweight neural network is also used to process the time series features in the key features; Decision-level fusion: Each sensor makes an independent judgment and then votes.

[0037] In an embodiment provided in the present application, dynamic threshold determination is performed in the embedded processing unit through a dynamic adaptive mechanism, specifically: Individualized threshold adjustment: Dynamically update alarm thresholds based on the patient's baseline data, including resting body temperature and daily stress fluctuation range; Time series context analysis: Combine historical data to determine the severity of the current event and perform early warning based on the judgment results.

[0038] Specifically, since the above sensors include pressure, chemical, temperature and other types, each sensor has different data characteristics. For example, a pressure sensor may provide continuous numerical changes, a chemical sensor may detect changes in the concentration of specific ions, and a temperature sensor monitors local temperature. Therefore, the fusion of these data requires processing time synchronization, data calibration, feature extraction and other issues. Therefore, this embodiment processes the above data in stages, and improves the accuracy and reliability of detection by integrating the complementary information of different sensors. Through the above design, this embodiment enables the embedded processing unit to achieve efficient and accurate multi-sensor data fusion in a resource-constrained environment, providing reliable real-time decision support for implantable infusion ports.

[0039] In an embodiment provided in the present application, the data analysis and warning module includes a real-time analysis unit, a hierarchical warning unit and an emergency response linkage unit; The real-time analysis unit is used to calculate the leakage risk index in real time based on the fusion result of the multi-sensor data to perform dynamic risk assessment; it also analyzes the change trend of the multi-sensor data over time through time series pattern recognition to distinguish acute leakage from chronic leakage; it is also used to exclude non-leakage events by filtering interference scenes; The graded warning unit is used to set the warning level and trigger conditions according to the severity of the leakage event, and associate different warning levels with corresponding treatment measures; the warning levels include level one warning, level two warning and level three warning; The emergency response linkage unit is used to perform equipment linkage, information push and emergency processing according to the warning level.

[0040] Specifically, the data analysis and early warning module of this embodiment adopts a hierarchical strategy that combines rule-driven and model-driven, taking into account both real-time and accuracy, and provides full-link safety protection from monitoring to emergency treatment for implantable infusion ports for cancer patients, thereby improving the timeliness of infusion port leakage monitoring and treatment and ensuring patient safety.

[0041] In one embodiment provided in the present application, the oncology implantable infusion port leakage monitoring system further includes a self-powered module for generating electricity using glucose or blood flow in the body, and combined with a micro lithium battery to extend the battery life of the monitoring device; The self-powered module includes a bioenergy collection unit, an energy storage unit, a power management unit and an energy status linkage unit; The bioenergy collection unit utilizes enzyme-catalyzed glucose oxidation reaction and oxygen reduction reaction to generate electrical energy; it also utilizes blood flow in blood vessels to drive micro-turbines or piezoelectric materials to generate electricity; The energy storage unit is used to store redundant power of the bioenergy collection unit for use during peak loads; The power management unit is used to dynamically assign energy source priorities and switch power supply modes and adjust power supply voltage according to load requirements; The energy status linkage unit is used to cooperate with the hierarchical warning mechanism of the hierarchical warning unit to trigger corresponding alarms when energy is insufficient and optimize power consumption to extend battery life.

[0042] Specifically, the self-powered module of this embodiment provides a sustainable and highly reliable energy supply solution for implantable medical devices through a full-link design of bioenergy harvesting-hybrid energy storage-intelligent power consumption management, and at the same time deeply collaborates with the graded early warning mechanism to ensure patient safety and system robustness.

[0043] Example 2 See also Figure 4 The present application embodiment provides a method for monitoring leakage of an implantable infusion port in oncology, which is applied to a system for monitoring leakage of an implantable infusion port in oncology as described above, and includes the following steps: Monitor pressure fluctuations in implanted infusion ports, sense temperature changes in surrounding tissues, and detect abnormal leakage of specific chemotherapy drug components to obtain multi-parameter sensor data; Biocompatible material packaging and integrated low-power chip are used to process the multi-parameter sensor data in real time; Conduct real-time analysis on the processed multi-parameter sensor data and issue graded warnings based on the analysis results; Using wireless communication technology to transmit the multi-parameter sensor data to an external terminal in real time; It uses glucose or blood flow in the body to generate electricity and combines it with a micro lithium battery to extend the battery life of the monitoring device.

[0044] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described or recorded in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0045] The technicians in the relevant field can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional units and modules is used as an example for illustration. In practical applications, the above-mentioned function allocation can be completed by different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiment can be integrated in a processing unit, or each unit can exist physically separately, or two or more units can be integrated in one unit. The above-mentioned integrated unit can be implemented in the form of hardware or in the form of software functional units. In addition, the specific names of the functional units and modules are only for the convenience of distinguishing each other, and are not used to limit the scope of protection of this application. The specific working process of the units and modules in the above-mentioned system can refer to the corresponding process in the aforementioned method embodiment, which will not be repeated here.

[0046] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present invention.

[0047] The above description is only a preferred embodiment of the present invention and does not limit the present invention in any form. Although the present invention has been disclosed as a preferred embodiment as above, it is not used to limit the present invention. Any technical personnel in this field can make some changes or modify the technical contents disclosed above into equivalent embodiments without departing from the scope of the technical solution of the present invention. However, any simple modification, equivalent change and modification made to the above embodiments according to the technical essence of the present invention without departing from the content of the technical solution of the present invention still fall within the scope of the technical solution of the present invention.

Claims

1. An implantable infusion port leakage monitoring system for oncology, characterized by: include: Multi-parameter sensor module: used to monitor pressure fluctuations in the implantable infusion port, sense changes in surrounding tissue temperature, and detect abnormal leakage of specific chemotherapy drug components, thereby obtaining multi-parameter sensor data; Flexible electronic circuit module: used for real-time processing of the multi-parameter sensor data; Data analysis and early warning module: used to analyze the processed multi-parameter sensor data in real time and issue graded early warnings based on the analysis results; Wireless communication module: used to transmit the multi-parameter sensor data to an external terminal in real time using wireless communication technology.

2. The oncology implantable infusion port leakage monitoring system according to claim 1, characterized in that: The multi-parameter sensor module includes a pressure sensor unit, a chemical sensor unit and a temperature sensor unit; The pressure sensor unit is used to monitor the pressure changes inside the implantable infusion port in real time and distinguish between infusion operations and leakage events through pressure fluctuation patterns; The chemical sensor unit is used to detect key indicators of chemotherapy drug leakage, including concentration of specific drug components and pH changes, and to distinguish drug leakage from body fluid leakage; The temperature sensor unit is used to sense the temperature abnormality of the tissue around the implantable infusion port and combine the pressure data / chemical data to eliminate the interference of non-leakage heating.

3. The oncology implantable infusion port leakage monitoring system according to claim 2, characterized in that: The multi-parameter sensor module also includes a flow sensor unit and a bioimpedance sensor unit; The flow sensor unit is used to monitor the liquid flow rate in the infusion pipeline, and triggers an early warning signal if the liquid flow rate increases or decreases abnormally; it is also linked with the pressure sensor to distinguish leakage events from mechanical failures; The bioimpedance sensor unit is used to monitor the impedance changes of the tissues around the implantable infusion port and evaluate the degree of damage to the local tissues caused by leakage.

4. The oncology implantable infusion port leakage monitoring system according to claim 1, characterized in that: The flexible electronic circuit module includes a data preprocessing unit, an analog-to-digital conversion unit and an embedded processing unit; The data preprocessing unit is used to denoise, filter and amplify the original signal in the multi-parameter sensor data to generate an analog signal, specifically: processing the signal-to-noise ratio through a low-noise amplifier and an adaptive filtering circuit, and adjusting the amplitude of the original signal to adapt to the input range of the analog-to-digital converter; The analog-to-digital conversion unit is used to convert the conditioned analog signal into a digital signal, specifically: time-division multiplexing sampling of the original signal at a high rate; converting the analog quantity into a digital signal through quantization and encoding; The embedded processing unit runs a leakage detection algorithm based on the digital signal to perform multi-sensor data fusion, dynamic threshold judgment and early warning decision-making.

5. The oncology implantable infusion port leakage monitoring system according to claim 4, characterized in that: The multi-sensor data fusion is performed in the embedded processing unit, specifically: Feature extraction: extracting key features for distinguishing a leakage state from a normal state from the digital signal; Multimodal fusion: primary fusion based on rules and primary logic judgment; secondary fusion based on machine learning models and secondary model judgment; if it is not determined as a leakage event in the primary logic judgment, it will enter the secondary model judgment, specifically: In the first-level logic judgment, if the conditions of pressure drop, pH deviation and local temperature rise are met at the same time, it is judged as a leakage event, otherwise it enters the second-level model judgment; Among them, the key features include pressure change slope, pressure fluctuation variance, pH value offset, specific ion concentration gradient, local temperature rise rate, temperature transient peak and multi-sensor temperature difference.

6. The oncology implantable infusion port leakage monitoring system according to claim 5, characterized in that: In the multimodal fusion, secondary fusion is performed based on a machine learning model, including: Feature-level fusion: concatenate the feature vectors of the key features into a unified input; Model selection: Random forest is used for embedded deployment to support the importance assessment of the key features; lightweight neural network is also used to process the time series features in the key features; Decision-level fusion: Each sensor makes an independent judgment and then votes.

7. The oncology implantable infusion port leakage monitoring system according to claim 4, characterized in that: In the embedded processing unit, dynamic threshold determination is performed through a dynamic adaptive mechanism, specifically: Individualized threshold adjustment: Dynamically update alarm thresholds based on the patient's baseline data, including resting body temperature and daily stress fluctuation range; Time series context analysis: Combine historical data to determine the severity of the current event and perform early warning based on the judgment results.

8. The oncology implantable infusion port leakage monitoring system according to claim 1, characterized in that: The data analysis and early warning module includes a real-time analysis unit, a hierarchical early warning unit and an emergency response linkage unit; The real-time analysis unit is used to calculate the leakage risk index in real time based on the fusion result of the multi-sensor data to perform dynamic risk assessment; it also analyzes the change trend of the multi-sensor data over time through time series pattern recognition to distinguish acute leakage from chronic leakage; it is also used to exclude non-leakage events by filtering interference scenes; The graded warning unit is used to set the warning level and trigger conditions according to the severity of the leakage event, and associate different warning levels with corresponding treatment measures; the warning levels include level one warning, level two warning and level three warning; The emergency response linkage unit is used to perform equipment linkage, information push and emergency processing according to the warning level.

9. The oncology implantable infusion port leakage monitoring system according to claim 1, characterized in that: The oncology implantable infusion port leakage monitoring system also includes a self-powered module for generating electricity using glucose or blood flow in the body, and combined with a micro lithium battery to extend the battery life of the monitoring device; The self-powered module includes a bioenergy collection unit, an energy storage unit, a power management unit and an energy status linkage unit; The bioenergy collection unit utilizes enzyme-catalyzed glucose oxidation reaction and oxygen reduction reaction to generate electrical energy; it also utilizes blood flow in blood vessels to drive micro-turbines or piezoelectric materials to generate electricity; The energy storage unit is used to store redundant power of the bioenergy collection unit for use during peak loads; The power management unit is used to dynamically assign energy source priorities and switch power supply modes and adjust power supply voltage according to load requirements; The energy status linkage unit is used to cooperate with the hierarchical warning mechanism of the hierarchical warning unit to trigger corresponding alarms when energy is insufficient and optimize power consumption to extend battery life.

10. A method for monitoring leakage of an implantable infusion port in oncology, applied to a system for monitoring leakage of an implantable infusion port in oncology as claimed in any one of claims 1 to 9, characterized in that: The steps include: Monitor pressure fluctuations in implanted infusion ports, sense temperature changes in surrounding tissues, and detect abnormal leakage of specific chemotherapy drug components to obtain multi-parameter sensor data; Processing the multi-parameter sensor data in real time; Conduct real-time analysis on the processed multi-parameter sensor data and issue graded warnings based on the analysis results; Using wireless communication technology to transmit the multi-parameter sensor data to an external terminal in real time; It uses glucose or blood flow in the body to generate electricity and combines it with a micro lithium battery to extend the battery life of the monitoring device.

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