Catheter state monitoring method and device based on intelligent algorithm control

Abstract

The invention provides a catheter state monitoring method and device based on intelligent algorithm control, and the method comprises the steps: collecting urine parameters through a plurality of embedded sensors, and transmitting the urine parameters to a health state detection module through a low-power-consumption wireless transmission module; the urine state detection module detects the change trend of the urine state by using a loss function based on a time sequence in combination with the multi-dimensional data of the urine parameters collected by the plurality of embedded sensors, and detects the abnormal change in the urine parameters; if the abnormal change is detected, the abnormal change is sent to a medical terminal through the low-power-consumption wireless transmission module; the degradation execution module receives a degradation instruction sent by the medical terminal and triggers the decomposition process of the catheter degradation material, according to the scheme, the degradation triggering time is dynamically adjusted through an algorithm, and it is ensured that the catheter is safely decomposed after the function is completed.

Description

Technical Field

[0001] The present invention belongs to the field of medical detection, and in particular relates to a method and device for monitoring the state of a urinary catheter based on intelligent algorithm control. Background Art

[0002] The urinary catheter is a medical device widely used in clinical medicine, mainly used to solve the urine excretion disorder of patients, postoperative care and urine drainage needs of long-term bedridden patients. However, the traditional urinary catheter has the following technical difficulties during use: The risk of infection is high. Long-term implantation of catheters in the body can easily lead to urinary tract infections (CAUTI). This is because bacteria adhere to the surface of the catheter and form a biofilm, which significantly increases the probability of infection. The existing technology uses antibacterial coatings or regularly replaces catheters to reduce the risk, but the effect is limited and increases medical costs and patient discomfort.

[0003] Catheter obstruction problem: Long-term use of catheters may cause obstruction due to urine crystal deposition or biofilm formation, affecting the normal urine drainage function. Existing solutions mostly rely on external cleaning or replacement of catheters, which has the problem of frequent intervention and complex operation.

[0004] Trauma during catheter removal: Traditional catheters need to be removed manually, which may cause discomfort to the patient or even urethral injury during the operation. Especially for patients who use it for a long time, the safety and comfort of the removal process become key issues.

[0005] Insufficient control over material degradation. Some studies have begun to try to use biodegradable materials to make urinary catheters, but in actual applications, it is difficult to accurately control the material degradation time. Degradation too early may cause the catheter to break before completing the drainage task, while degradation too late will lose its meaning and may even produce residues that cause secondary damage to urinary tract health.

[0006] In recent years, with the rapid development of Internet of Things (IoT) technology and artificial intelligence (AI), smart medical devices have gradually attracted attention. Some studies have tried to embed sensors and algorithms into catheters to monitor urine flow, pH value, temperature and other data to provide support for infection warning. However, existing technologies still have the following problems: The data monitoring function is limited and the trigger time of material degradation cannot be adjusted dynamically.

[0007] The lack of intelligent algorithms to comprehensively analyze patients’ individual characteristics makes it difficult to provide customized treatment for different patients.

[0008] Remote monitoring and real-time feedback functions are insufficient, and the collaboration capabilities between medical terminals and catheters are limited. Summary of the invention

[0009] In view of this, the present invention provides a method for monitoring the state of a urinary catheter based on intelligent algorithm control, characterized in that the method is applied to a urinary catheter, comprising: The embedded sensor module collects urine parameters through multiple embedded sensors and sends them to the health status detection module through a low-power wireless transmission module; The urine status detection module combines the multi-dimensional data of the urine parameters collected by the multiple embedded sensors, uses a loss function based on a time series to detect the change trend of the urine status, and detects abnormal changes in the urine parameters; if the abnormal change is detected, it is sent to the medical terminal through the low-power wireless transmission module; The degradation execution module receives the degradation instruction issued by the medical terminal, triggering the decomposition process of the degradable material of the catheter; the degradation instruction includes a degradation time window corresponding to the embedded sensor, and the degradation time window is calculated and generated by the degradation control algorithm module of the medical terminal to ensure that the degradation process of the catheter is started within the degradation time window.

[0010] In particular, the urine state detection module uses a time series-based loss function to detect the change trend of urine state. The time series-based loss function is expressed as: ,in, is the time step When the embedded sensor The characteristics of the collected urine state, is the length of the time series, is the balance weight parameter.

[0011] In particular, the medical terminal performs real-time evaluation based on the abnormal changes in urine, generates a health status report based on the analysis results, and synchronizes the health status report to the patient or medical staff's mobile terminal through the cloud platform.

[0012] In particular, the degradation control algorithm module uses the neighborhood attention mechanism model to calculate the correlation weights of the multidimensional data between embedded sensors to measure the impact of each sensor data on the degradation triggering process of the catheter, combines the degradation time prediction model to analyze the time series data, and dynamically predicts the degradation time window of the catheter.

[0013] In particular, the degradation control algorithm module uses the neighborhood attention mechanism model to calculate the correlation weights of the multidimensional data collected between multiple embedded sensors to measure the impact of each embedded sensor data on the degradation triggering process of the catheter, specifically including: according to the urine parameters collected by each embedded sensor, calculating its weight value in the urine environment change to measure the impact of each embedded sensor data on the degradation triggering process of the catheter, and the calculation method is: ,in, For embedded sensors and its neighborhood embedded sensors In the The weight in the iteration; Represents embedded sensor The neighborhood set of embedded sensors The neighborhood set of all directly connected embedded sensors, Represents embedded sensor Any neighboring node of ; represents the activation function, Represents embedded sensor In the The characteristic state of the iteration, Represents embedded sensor j In the The characteristic state of the iteration; For embedded sensors and The edge features between For embedded sensors and any neighborhood embedded sensors j The edge features between Indicates the characteristic state of the embedded sensor and a weight matrix mapped to a specific projection space associated with the catheter sensor features; represents a weight matrix that maps edge features to a specific projection space associated with catheter sensor features; The attention vector represents the calculation of the attention score in a specific projection space related to the catheter sensor characteristics; wherein the degradation trigger time of the catheter material is dynamically adjusted according to the urine parameters to ensure the accuracy and safety of the degradation process.

[0014] In particular, the neighborhood attention mechanism model ranks the importance weights of the multiple embedded sensors; the degradation time prediction model is used to adjust the data of each embedded sensor through the importance weight to form a set of dynamic feature vectors as input features, use the long short-term memory network LSTM to capture the long-term dependencies in the time series, predict the changing trend of urine environmental parameters, and use a fully connected network in the output layer to generate the degradation time window.

[0015] In particular, the urine parameters include urine flow rate, pH value, temperature and specific biomarker concentration, which are collected by different embedded sensors respectively, and the abnormal changes in the urine parameters include abnormal flow rate, abnormal temperature fluctuation, abnormal pH value fluctuation or abnormal urine enzyme concentration fluctuation.

[0016] In particular, the catheter includes a three-layer structure of an outer layer, an intermediate layer and a core material layer. The catheter also includes an electrical stimulation module, which is used to first activate the outer layer material of the catheter to start dissolving when the degradation of the catheter begins; the intermediate layer stores catalytic chemical reagents, and the electrical stimulation module adjusts the micropores in the intermediate layer to control the release rate of the catalytic chemical reagents; the catalyst diffuses to the core material layer; when the catalytic chemical reagents react with the core layer material, the core material layer is eventually decomposed into non-toxic small molecules.

[0017] In particular, when the outer layer dissolves, it can also release an auxiliary trigger, which is a small molecule compound used to accelerate the release of the catalyst in the middle layer.

[0018] The present invention also discloses a urinary catheter device for realizing state monitoring based on intelligent algorithm control, the device comprising: An embedded sensor module is used to collect urine parameters through multiple embedded sensors and send them to the health status detection module through a low-power wireless transmission module; A urine status detection module, which is used to combine the multi-dimensional data of the urine parameters collected by the multiple embedded sensors, use a time series-based loss function to detect the change trend of the urine status, and detect abnormal changes in the urine parameters; if the abnormal change is detected, it is sent to the medical terminal through the low-power wireless transmission module; The degradation execution module is used to receive the degradation instruction issued by the medical terminal and trigger the decomposition process of the degradable material of the catheter; the degradation instruction includes a degradation time window corresponding to the embedded sensor, and the degradation time window is calculated and generated by the degradation control algorithm module of the medical terminal to ensure that the catheter is decomposed into non-toxic small molecules within the degradation time window and excreted from the body through urine.

[0019] Beneficial effects: Based on the above problems, the present invention proposes a biodegradable urinary catheter and its state monitoring method based on intelligent algorithm control, innovatively combining intelligent sensor networks, neighborhood attention mechanism models and reinforcement learning algorithms to dynamically monitor urine environmental characteristics and accurately control the degradation time and state of the urinary catheter. Through the coordinated optimization of medical terminals and urinary catheters, the following goals are achieved: Early warning of infection: Real-time monitoring of urine composition, identification of infection risks and sending alerts to reduce the occurrence of complications.

[0020] Intelligent degradation: Dynamically adjust the degradation trigger time through an algorithm to ensure that the catheter decomposes safely after its function is completed.

[0021] Personalized optimization: Adjust alarm thresholds and degradation parameters based on the patient's specific physiological characteristics to improve adaptability and comfort.

[0022] Reduce manual intervention: Through automated design, the workload of medical staff is reduced, while reducing the pain and potential trauma of patients.

[0023] The present invention is committed to improving the intelligence level of the urinary catheter, providing a new solution for the medical industry, and effectively solving the limitations of the use of traditional urinary catheters. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Figure 1 This is a flow chart of the method for monitoring the state of a urinary catheter based on intelligent algorithm control proposed in the present invention; Figure 2 The invention provides a urinary catheter device that realizes state monitoring based on intelligent algorithm control. DETAILED DESCRIPTION

[0025] The present invention is described in detail below with reference to the accompanying drawings and embodiments.

[0026] The present invention provides a method for monitoring the state of a urinary catheter based on intelligent algorithm control, such as Figure 1 As shown, the method is applied to a urinary catheter and comprises: The embedded sensor module collects urine parameters through multiple embedded sensors and sends them to the health status detection module through a low-power wireless transmission module; the urine parameters include urine flow rate, pH value, temperature and specific biomarker concentration, which are collected by different embedded sensors respectively. In this embodiment, multiple micro sensors are arranged on the surface and inside of the catheter for multi-point monitoring to monitor different environmental parameters. The following different sensors are included: pH sensor: detects changes in urine pH.

[0027] Temperature sensor: measures local temperature.

[0028] Enzyme concentration sensor: senses the concentration of specific enzymes in urine.

[0029] Flow rate sensor: Evaluates urine flow rate to determine if there is a blockage or other abnormality.

[0030] The abnormal changes in the urine parameters include abnormal flow rate, abnormal temperature fluctuation, abnormal pH value fluctuation or abnormal urine enzyme concentration fluctuation. The urine state detection module combines the multi-dimensional data of the urine parameters collected by the multiple embedded sensors, and uses a loss function based on a time series to detect the changing trend of the urine state and the abnormal changes in the urine parameters; if the abnormal change is detected, it is sent to the medical terminal through the low-power wireless transmission module; the urine state detection module uses a loss function based on a time series to detect the changing trend of the urine state, and the loss function based on a time series is expressed as: ,in, is the time step When the embedded sensor The characteristics of the collected urine state, is the length of the time series, is the balance weight parameter.

[0031] The degradation execution module receives the degradation instruction issued by the medical terminal, triggering the decomposition process of the degradable material of the catheter; the degradation instruction includes a degradation time window corresponding to the embedded sensor, and the degradation time window is calculated and generated by the degradation control algorithm module of the medical terminal to ensure that the degradation process of the catheter is started within the degradation time window.

[0032] The medical terminal performs real-time evaluation based on the abnormal changes in urine, generates a health status report based on the analysis results, and synchronizes the health status report to the patient or medical staff's mobile terminal through the cloud platform.

[0033] The degradation control algorithm module uses the neighborhood attention mechanism model to calculate the correlation weights of the multidimensional data between the embedded sensors to measure the impact of each sensor data on the degradation triggering process of the catheter, and combines the degradation time prediction model to analyze the time series data to dynamically predict the degradation time window of the catheter. The degradation control algorithm module uses the neighborhood attention mechanism model to calculate the correlation weights of the multidimensional data collected between multiple embedded sensors to measure the impact of each embedded sensor data on the degradation triggering process of the catheter.

[0034] In this embodiment, first, data collection and neighborhood attention mechanism calculation are performed, and the embedded sensor collects multi-dimensional data of the urine environment (such as pH value, enzyme concentration, urine flow rate, etc.) in real time.

[0035] According to the urine parameters collected by each embedded sensor, its weight value in the urine environment change is calculated to measure the impact of each embedded sensor data on the catheter degradation triggering process. The calculation method is: ,in, For embedded sensors and its neighborhood embedded sensors In the The weight in the iteration; Represents embedded sensor The neighborhood set of embedded sensors The neighborhood set of all directly connected embedded sensors, Represents embedded sensor Any neighboring node of ; represents the activation function, Represents embedded sensor In the The characteristic state of the iteration, Represents embedded sensor j In the The characteristic state of the iteration; For embedded sensors and The edge features between For embedded sensors and any neighborhood embedded sensors j The edge features between Indicates the characteristic state of the embedded sensor and a weight matrix mapped to a specific projection space associated with the catheter sensor features; represents a weight matrix that maps edge features to a specific projection space associated with catheter sensor features; represents the attention vector that calculates the attention score in a specific projection space related to the catheter sensor characteristics; wherein the degradation trigger time of the catheter material is dynamically adjusted according to the urine parameters to ensure the accuracy and safety of the degradation process. Through this formula, the dynamic weight allocation of embedded sensor data can effectively reflect the overall trend of urine environment changes, provide a scientific basis for catheter degradation triggering, and avoid triggering errors caused by local environmental characteristics.

[0036] Using Sensor Weights Weighting sensor data to generate time series input

[0037] Then, time series modeling and degradation time window prediction are performed, and the output of the neighborhood attention model is Input to LSTM / GRU model: Capture dynamic trends in multi-time step data, such as whether the pH drop is stable. Whether the enzyme concentration reaches the threshold that triggers degradation. Capture long-term changes in environmental characteristics through memory cells.

[0038] At the output layer of LSTM, the degradation trigger time window [ , ]: ,in It is the degradation time range that is dynamically adjusted according to environmental conditions.

[0039] Finally, the degradation trigger time is dynamically adjusted, according to the predicted degradation time window [ , ]Dynamically generate degradation trigger instructions: If the current time is close to , a trigger signal is sent to the catheter via wireless communication. The system monitors the degradation process and evaluates the urine environment in real time. If the abnormality is not resolved, the duration can be appropriately extended or shortened. , ].

[0040] For example: Input data: Real-time sensor data:

[0041] Prediction process: Neighborhood attention mechanism calculation weight: α t3 =0.5, so the sensor characteristics of t3 are given priority.

[0042] Time series forecasting model analysis trends: The pH is trending downward and degradation may need to be triggered earlier.

[0043] The increase in enzyme concentration supports further maturation of degradation conditions.

[0044] Output: The degradation trigger time window is predicted to be { [ =After 3 hours, =5 hours later]}.

[0045] exist When the degradation module is triggered, it starts.

[0046] The neighborhood attention mechanism model sorts the importance weights of the multiple embedded sensors; the degradation time prediction model is used to adjust the data of each embedded sensor through the importance weight to form a set of dynamic feature vectors as input features, use the long short-term memory network LSTM to capture the long-term dependencies in the time series, predict the changing trend of urine environmental parameters, and use a fully connected network in the output layer to generate the degradation time window.

[0047] In this embodiment, the catheter includes a three-layer structure of an outer layer, an intermediate layer and a core material layer. The catheter also includes an electrical stimulation module, which is used to first activate the outer layer material of the catheter to start dissolving when the degradation of the catheter begins; the intermediate layer stores catalytic chemical reagents, and the electrical stimulation module adjusts the micropores in the intermediate layer to control the release rate of the catalytic chemical reagents; the catalyst diffuses to the core material layer; when the catalytic chemical reagents react with the core layer material, the core material layer is eventually decomposed into non-toxic small molecules.

[0048] For example: Triggering the degradation process is as follows: T=0: The medical terminal sends a signal to activate the dissolution of the outer layer material.

[0049] T = 5 minutes: The outer layer dissolves, exposing the middle layer and releasing the catalyst.

[0050] T=10 minutes: The core layer begins to gradually degrade, and the sensor monitors the degradation rate.

[0051] T=30 minutes: The core layer is completely decomposed and the bottom layer begins to disintegrate.

[0052] T=45 minutes: All materials are excreted in urine, completing the degradation process.

[0053] When the outer layer dissolves, it can also release auxiliary triggers, which are small molecule compounds used to accelerate the release of the catalyst in the middle layer. The middle layer of the catheter can store a variety of catalysts: Enzyme catalysts (such as urease): highly specific and used to decompose core materials.

[0054] Acid catalysts (such as slow-release weak acids): Lower the pH to accelerate the hydrolysis of the material.

[0055] Optionally, the medical terminal determines the release order of catalyst types based on sensor feedback. For example, if the enzyme concentration is insufficient but the pH value is high, the acid catalyst is released first. When the enzyme concentration increases, it is switched to the enzyme catalyst to improve the degradation efficiency.

[0056] The present invention also discloses a urinary catheter device for realizing state monitoring based on intelligent algorithm control, such as Figure 2 As shown, the device comprises: The embedded sensor module is used to collect urine parameters through multiple embedded sensors and send them to the health status detection module through a low-power wireless transmission module; the embedded sensor module collects urine parameters through multiple embedded sensors and sends them to the health status detection module through a low-power wireless transmission module; the urine parameters include urine flow rate, pH value, temperature and specific biomarker concentration, which are collected by different embedded sensors respectively. In this embodiment, multiple micro sensors are arranged on the surface and inside of the catheter for multi-point monitoring to monitor different environmental parameters. It includes the following different sensors: pH sensor: detects changes in urine pH.

[0057] Temperature sensor: measures local temperature.

[0058] Enzyme concentration sensor: senses the concentration of specific enzymes in urine.

[0059] Flow rate sensor: Evaluates urine flow rate to determine if there is a blockage or other abnormality.

[0060] The abnormal changes in the urine parameters include abnormal flow rate, abnormal temperature fluctuation, abnormal pH value fluctuation or abnormal urine enzyme concentration fluctuation. The urine state detection module combines the multi-dimensional data of the urine parameters collected by the multiple embedded sensors, and uses a loss function based on a time series to detect the changing trend of the urine state and the abnormal changes in the urine parameters; if the abnormal change is detected, it is sent to the medical terminal through the low-power wireless transmission module; the urine state detection module uses a loss function based on a time series to detect the changing trend of the urine state, and the loss function based on a time series is expressed as: ,in, is the time step When the embedded sensor The characteristics of the collected urine state, is the length of the time series, is the balance weight parameter.

[0061] The degradation execution module is used to receive the degradation instruction issued by the medical terminal and trigger the decomposition process of the degradable material of the catheter; the degradation instruction includes a degradation time window corresponding to the embedded sensor, and the degradation time window is calculated and generated by the degradation control algorithm module of the medical terminal to ensure that the catheter is decomposed into non-toxic small molecules within the degradation time window and excreted from the body through urine.

[0062] The degradation execution module receives the degradation instruction issued by the medical terminal, triggering the decomposition process of the degradable material of the catheter; the degradation instruction includes a degradation time window corresponding to the embedded sensor, and the degradation time window is calculated and generated by the degradation control algorithm module of the medical terminal to ensure that the degradation process of the catheter is started within the degradation time window.

[0063] The medical terminal performs real-time evaluation based on the abnormal changes in urine, generates a health status report based on the analysis results, and synchronizes the health status report to the patient or medical staff's mobile terminal through the cloud platform.

[0064] The degradation control algorithm module uses the neighborhood attention mechanism model to calculate the correlation weights of the multidimensional data between the embedded sensors to measure the impact of each sensor data on the degradation triggering process of the catheter, and combines the degradation time prediction model to analyze the time series data to dynamically predict the degradation time window of the catheter. The degradation control algorithm module uses the neighborhood attention mechanism model to calculate the correlation weights of the multidimensional data collected between multiple embedded sensors to measure the impact of each embedded sensor data on the degradation triggering process of the catheter.

[0065] In this embodiment, first, data collection and neighborhood attention mechanism calculation are performed, and the embedded sensor collects multi-dimensional data of the urine environment (such as pH value, enzyme concentration, urine flow rate, etc.) in real time.

[0066] According to the urine parameters collected by each embedded sensor, its weight value in the urine environment change is calculated to measure the impact of each embedded sensor data on the catheter degradation triggering process. The calculation method is: ,in, For embedded sensors and its neighborhood embedded sensors In the The weight in the iteration; Represents embedded sensor The neighborhood set of embedded sensors The neighborhood set of all directly connected embedded sensors, Represents embedded sensor Any neighboring node of ; represents the activation function, Represents embedded sensor In the The characteristic state of the iteration, Represents embedded sensor j In the The characteristic state of the iteration; For embedded sensors and The edge features between For embedded sensors and any neighborhood embedded sensors j The edge features between Indicates the characteristic state of the embedded sensor and a weight matrix mapped to a specific projection space associated with the catheter sensor features; represents a weight matrix that maps edge features to a specific projection space associated with catheter sensor features; represents the attention vector that calculates the attention score in a specific projection space related to the catheter sensor characteristics; wherein the degradation trigger time of the catheter material is dynamically adjusted according to the urine parameters to ensure the accuracy and safety of the degradation process. Through this formula, the dynamic weight allocation of embedded sensor data can effectively reflect the overall trend of urine environment changes, provide a scientific basis for catheter degradation triggering, and avoid triggering errors caused by local environmental characteristics.

[0067] Using Sensor Weights Weighting sensor data to generate time series input , Then, time series modeling and degradation time window prediction are performed, and the output of the neighborhood attention model is Input to LSTM / GRU model: Capture dynamic trends in multi-time step data, such as whether the pH drop is stable. Whether the enzyme concentration reaches the threshold that triggers degradation. Capture long-term changes in environmental characteristics through memory cells.

[0068] At the output layer of LSTM, the degradation trigger time window [ , ]: ,in It is the degradation time range that is dynamically adjusted according to environmental conditions.

[0069] Finally, the degradation trigger time is dynamically adjusted, according to the predicted degradation time window [ , ]Dynamically generate degradation trigger instructions: If the current time is close to , a trigger signal is sent to the catheter via wireless communication. The system monitors the degradation process and evaluates the urine environment in real time. If the abnormality is not resolved, the duration can be appropriately extended or shortened. , ].

[0070] For example: Input data: Real-time sensor data:

[0071] Prediction process: Neighborhood attention mechanism calculation weight: α t3 =0.5, so the sensor characteristics of t3 are given priority.

[0072] Time series forecasting model analysis trends: The pH is trending downward and degradation may need to be triggered earlier.

[0073] The increase in enzyme concentration supports further maturation of degradation conditions.

[0074] Output: The degradation trigger time window is predicted to be { [ =3 hours later, tend=5 hours later]}.

[0075] exist When the degradation module is triggered, it starts.

[0076] The neighborhood attention mechanism model sorts the importance weights of the multiple embedded sensors; the degradation time prediction model is used to adjust the data of each embedded sensor through the importance weight to form a set of dynamic feature vectors as input features, use the long short-term memory network LSTM to capture the long-term dependencies in the time series, predict the changing trend of urine environmental parameters, and use a fully connected network in the output layer to generate the degradation time window.

[0077] In this embodiment, the catheter includes a three-layer structure of an outer layer, an intermediate layer and a core material layer. The catheter also includes an electrical stimulation module, which is used to first activate the outer layer material of the catheter to start dissolving when the degradation of the catheter begins; the intermediate layer stores catalytic chemical reagents, and the electrical stimulation module adjusts the micropores in the intermediate layer to control the release rate of the catalytic chemical reagents; the catalyst diffuses to the core material layer; when the catalytic chemical reagents react with the core layer material, the core material layer is eventually decomposed into non-toxic small molecules.

[0078] For example: Triggering the degradation process is as follows: T=0: The medical terminal sends a signal to activate the dissolution of the outer layer material.

[0079] T = 5 minutes: The outer layer dissolves, exposing the middle layer and releasing the catalyst.

[0080] T=10 minutes: The core layer begins to gradually degrade, and the sensor monitors the degradation rate.

[0081] T=30 minutes: The core layer is completely decomposed and the bottom layer begins to disintegrate.

[0082] T=45 minutes: All materials are excreted in urine, completing the degradation process.

[0083] When the outer layer dissolves, it can also release auxiliary triggers, which are small molecule compounds used to accelerate the release of the catalyst in the middle layer. The middle layer of the catheter can store a variety of catalysts: Enzyme catalysts (such as urease): highly specific and used to decompose core materials.

[0084] Acid catalysts (such as slow-release weak acids): Lower the pH to accelerate the hydrolysis of the material.

[0085] Optionally, the medical terminal determines the release order of catalyst types based on sensor feedback. For example, if the enzyme concentration is insufficient but the pH value is high, the acid catalyst is released first. When the enzyme concentration increases, it is switched to the enzyme catalyst to improve the degradation efficiency.

[0086] The present invention also discloses a method for monitoring the state of a urinary catheter based on intelligent algorithm control, which is applied to a medical terminal and includes: The data acquisition module receives abnormal changes in urine parameters sent by the urinary catheter through the low-power wireless transmission module; The health monitoring module performs real-time evaluation based on the abnormal changes in urine and generates a health status report based on the analysis results; The degradation control algorithm module calculates the weight value of each embedded sensor in the change of urine environment according to the urine parameters collected by each embedded sensor in the catheter; measures the influence of each embedded sensor data on the degradation triggering process of the catheter, dynamically predicts the degradation time window corresponding to the embedded sensor, and generates degradation instructions according to the degradation time window; The data interaction module sends the degradation instruction to the catheter to ensure that the catheter is decomposed into non-toxic small molecules within the degradation time window and is excreted from the body through urine.

[0087] The medical terminal performs real-time evaluation based on the abnormal changes in urine, generates a health status report based on the analysis results, and synchronizes the health status report to the patient or medical staff's mobile terminal through the cloud platform.

[0088] In summary, the above are only preferred embodiments of the present invention and are not intended to limit the protection scope of the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

[0089] It is obvious to those skilled in the art that the embodiments of the present invention are not limited to the details of the above exemplary embodiments, and that the embodiments of the present invention can be implemented in other specific forms without departing from the spirit or basic features of the embodiments of the present invention. Therefore, from any point of view, the embodiments should be regarded as exemplary and non-restrictive, and the scope of the embodiments of the present invention is limited by the attached claims rather than the above description, so it is intended to include all changes that fall within the meaning and scope of the equivalent elements of the claims in the embodiments of the present invention. Any figure mark in the claims should not be regarded as limiting the claims involved. In addition, it is obvious that the word "comprising" does not exclude other units or steps, and the singular does not exclude the plural. Multiple units, modules or devices stated in the system, device or terminal claims can also be implemented by the same unit, module or device through software or hardware. The words first, second, etc. are used to indicate names, and do not indicate any particular order.

[0090] Finally, it should be noted that the above implementation modes are only used to illustrate the technical solutions of the embodiments of the present invention and are not intended to limit them. Although the embodiments of the present invention have been described in detail with reference to the above preferred implementation modes, those skilled in the art should understand that the technical solutions of the embodiments of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for monitoring the state of a urinary catheter based on intelligent algorithm control, characterized in that: The method is applied to urinary catheters and includes: The embedded sensor module collects urine parameters through multiple embedded sensors and sends them to the health status detection module through a low-power wireless transmission module; The urine status detection module combines the multi-dimensional data of the urine parameters collected by the multiple embedded sensors, uses a loss function based on a time series to detect the change trend of the urine status, and detects abnormal changes in the urine parameters; if the abnormal change is detected, it is sent to the medical terminal through the low-power wireless transmission module; The degradation execution module receives the degradation instruction issued by the medical terminal, triggering the decomposition process of the degradable material of the catheter; the degradation instruction includes a degradation time window corresponding to the embedded sensor, and the degradation time window is calculated and generated by the degradation control algorithm module of the medical terminal to ensure that the degradation process of the catheter is started within the degradation time window.

2. The method for monitoring the state of a urinary catheter based on intelligent algorithm control according to claim 1, characterized in that: The urine state detection module uses a time series-based loss function to detect the change trend of urine state. The loss function based on the time series is expressed as: ,in, is the time step When the embedded sensor The characteristics of the collected urine state, is the length of the time series, is the balance weight parameter.

3. The method for monitoring the state of a urinary catheter based on intelligent algorithm control according to claim 2, characterized in that: The medical terminal performs real-time evaluation based on the abnormal changes in urine, generates a health status report based on the analysis results, and synchronizes the health status report to the patient or medical staff's mobile terminal through the cloud platform.

4. The method for monitoring the state of a urinary catheter based on intelligent algorithm control according to claim 1, characterized in that: The degradation control algorithm module uses a neighborhood attention mechanism model to calculate the correlation weights of multidimensional data between embedded sensors to measure the impact of each sensor data on the degradation triggering process of the catheter, combines the degradation time prediction model to analyze the time series data, and dynamically predicts the degradation time window of the catheter.

5. The method for monitoring the state of a urinary catheter based on intelligent algorithm control according to claim 4, characterized in that: The degradation control algorithm module uses the neighborhood attention mechanism model to calculate the correlation weights of the multidimensional data collected between multiple embedded sensors to measure the impact of each embedded sensor data on the catheter degradation triggering process, specifically including: According to the urine parameters collected by each embedded sensor, its weight value in the urine environment change is calculated to measure the impact of each embedded sensor data on the catheter degradation triggering process. The calculation method is: ,in, For embedded sensors and its neighborhood embedded sensors In the The weight in the iteration; Represents embedded sensor The neighborhood set of embedded sensors The neighborhood set of all directly connected embedded sensors, Represents embedded sensor Any neighboring node of ; represents the activation function, Represents embedded sensor In the The feature state of the iteration, Represents embedded sensor j In the The characteristic state of the iteration; For embedded sensors and The edge features between For embedded sensors and any neighborhood embedded sensors j The edge features between Indicates the characteristic state of the embedded sensor and a weight matrix mapped to a specific projection space associated with the catheter sensor features; represents a weight matrix that maps edge features to a specific projection space associated with catheter sensor features; The attention vector represents the calculation of the attention score in a specific projection space related to the catheter sensor characteristics; wherein the degradation trigger time of the catheter material is dynamically adjusted according to the urine parameters to ensure the accuracy and safety of the degradation process.

6. The method for monitoring the state of a urinary catheter based on intelligent algorithm control according to claim 5, characterized in that: The neighborhood attention mechanism model sorts the importance weights of the multiple embedded sensors; the degradation time prediction model is used to adjust the data of each embedded sensor through the importance weight to form a set of dynamic feature vectors as input features, use the long short-term memory network LSTM to capture the long-term dependencies in the time series, predict the changing trend of urine environmental parameters, and use a fully connected network in the output layer to generate the degradation time window.

7. The method for monitoring the state of a urinary catheter based on intelligent algorithm control according to any one of claims 1 to 6, characterized in that: The urine parameters include urine flow rate, pH value, temperature and specific biomarker concentration, which are collected by different embedded sensors respectively. The abnormal changes in the urine parameters include abnormal flow rate, abnormal temperature fluctuation, abnormal pH value fluctuation or abnormal urine enzyme concentration fluctuation.

8. The method for monitoring the state of a urinary catheter based on intelligent algorithm control according to any one of claims 1 to 7, characterized in that: The urinary catheter comprises a three-layer structure of an outer layer, an intermediate layer and a core material layer, and the urinary catheter further comprises an electrical stimulation module for first activating the outer layer material of the urinary catheter to start dissolving when degradation of the urinary catheter begins; The intermediate layer stores a catalytic chemical reagent, and the electrical stimulation module adjusts the micropores in the intermediate layer to control the release rate of the catalytic chemical reagent; The catalyst diffuses into the core material layer; when the catalytic chemical reagent reacts with the core layer material, the core material layer is eventually decomposed into non-toxic small molecules.

9. The method for monitoring the state of a urinary catheter based on intelligent algorithm control according to claim 8, characterized in that: When the outer layer dissolves, it can also release an auxiliary trigger, which is a small molecule compound used to accelerate the release of the catalyst in the middle layer.

10. A urinary catheter device for state monitoring based on intelligent algorithm control, characterized in that: The device includes: An embedded sensor module is used to collect urine parameters through multiple embedded sensors and send them to the health status detection module through a low-power wireless transmission module; A urine status detection module, which is used to combine the multi-dimensional data of the urine parameters collected by the multiple embedded sensors, use a time series-based loss function to detect the change trend of the urine status, and detect abnormal changes in the urine parameters; if the abnormal change is detected, it is sent to the medical terminal through the low-power wireless transmission module; The degradation execution module is used to receive the degradation instruction issued by the medical terminal and trigger the decomposition process of the degradable material of the catheter; the degradation instruction includes a degradation time window corresponding to the embedded sensor, and the degradation time window is calculated and generated by the degradation control algorithm module of the medical terminal to ensure that the catheter is decomposed into non-toxic small molecules within the degradation time window and excreted from the body through urine.

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