A tracheal intubation temperature and humidity monitoring and control system

Abstract

The present invention discloses a temperature and humidity monitoring and control system for tracheal intubation, which relates to the technical field of medical devices. The system includes: an airway monitoring terminal; a device control terminal, which is used to establish communication connections with the tracheal monitoring terminal and the medical monitoring station, obtain the collected real-time temperature and humidity data, judge whether there are abnormal temperature and humidity in the tracheal intubation through data analysis, trigger an airway temperature and humidity abnormality warning according to the judgment result, and control the airway temperature and humidity regulation; a medical monitoring station. The present invention provides personalized temperature and humidity regulation and abnormality warning functions by real-time monitoring of the temperature and humidity changes in the tracheal intubation, combined with the patient's physiological signs and environmental data; has intelligent data analysis and prediction capabilities, can predict future temperature and humidity trends, automatically adjust the control parameters, and dynamically optimize according to the patient's signs and environmental conditions to ensure that the temperature and humidity are within the most suitable range, improving the patient's comfort and experience effect.

Description

Technical Field

[0001] The present invention relates to the technical field of medical devices, and particularly to a temperature and humidity monitoring and control system for endotracheal intubation. Background Art

[0002] With the continuous improvement of medical technology and treatment levels, the clinical demand for respiratory management devices has been increasing day by day. Especially in operations such as endotracheal intubation and tracheotomy, these devices play a crucial role in rescuing patients with respiratory dysfunction and maintaining the normal operation of vital signs. However, with the increasingly complex needs of patients for medical devices, traditional endotracheal intubation and tracheotomy tube products can no longer fully meet the requirements of modern medicine for high-precision and high-stability monitoring, especially for the monitoring of respiratory tract temperature and humidity.

[0003] Endotracheal intubation and tracheotomy are widely used in critically ill patients, especially in patients undergoing anesthesia, respiratory failure, or unable to breathe independently. These two operations can ensure unobstructed airways and provide effective ventilation support for patients. Endotracheal intubation is usually used for acute conditions or short-term treatments, while tracheotomy is mostly used for patients who require long-term mechanical ventilation, such as those with chronic respiratory failure, critically ill patients, or patients who need long-term ventilation management.

[0004] However, regardless of whether it is endotracheal intubation or tracheotomy, the postoperative respiratory tract management of patients is of crucial importance. The humidity and temperature of the patient's respiratory tract not only directly affect the patency of the airway, but also have a profound impact on the rehabilitation process, prevention of complications, and treatment effects. For example, during endotracheal intubation or tracheotomy, the respiratory tract is often exposed to the external environment, and drastic changes in airway temperature and humidity may trigger a series of adverse reactions, such as airway dryness, thick sputum, and upper respiratory tract injury.

[0005] Although endotracheal intubation and tracheotomy have been widely used, most endotracheal intubation and tracheotomy tube products on the market lack the function of real-time temperature and humidity monitoring. Currently, the existing products on the market are usually limited to the monitoring of traditional parameters such as airway patency, air flow, and air pressure, and the real-time tracking and control of respiratory tract temperature and humidity are relatively weak. This makes it difficult for medical staff to grasp the changes in the patient's respiratory tract temperature and humidity in a timely manner after the operation and unable to take intervention measures promptly.

[0006] In addition, although some existing temperature and humidity monitoring devices have certain monitoring functions, their accuracy and stability still cannot meet the requirements of clinical applications. Some devices have problems such as inaccurate monitoring, data delay, and insufficient accuracy, making it difficult to accurately reflect the true condition of the patient's respiratory tract. For complex or patients with large changes, the lag and inaccuracy of monitoring results may lead to treatment delays and even complications, increasing the risk to patients. Summary of the Invention

[0007] Based on this, it is necessary to provide a temperature and humidity monitoring and control system for endotracheal intubation in view of the above technical problems.

[0008] The present invention provides a temperature and humidity monitoring and control system for endotracheal intubation, and the system includes:

[0009] An airway monitoring terminal, which is used to be installed on the endotracheal intubation tube wall, to monitor the temperature and humidity changes inside the endotracheal intubation in real time, obtain real-time temperature and humidity data, and integrate data display and transmission functions to synchronously display and transmit the data information of the real-time temperature and humidity data;

[0010] A device control terminal, which is used to establish a communication connection with the airway monitoring terminal and the medical monitoring station, obtain the collected real-time temperature and humidity data, judge whether there is abnormal temperature and humidity inside the endotracheal intubation through data analysis, and trigger an airway temperature and humidity abnormal warning and control airway temperature and humidity regulation according to the judgment result;

[0011] A medical monitoring station, which is used to establish a communication connection with the device control terminal, obtain the monitoring data and operating status of all airway monitoring terminals and device control terminals in the monitoring area, display them in real time through a visualization device, and centrally store and manage the monitoring data;

[0012] Further, the airway monitoring terminal includes: a waterproof coating module, a detection sensor module, a fixed protection module, an integrated display module, a power supply module, and an external interface module;

[0013] Among them, the waterproof coating module is used to protect electronic components from moisture and liquid intrusion, and maintain the long-term stable operation of electronic components in the humid environment inside the endotracheal intubation;

[0014] The detection sensor module is used to integrate a temperature sensor and a humidity sensor to monitor the temperature and humidity status and changes inside the endotracheal intubation in real time, and obtain real-time temperature and humidity data;

[0015] The fixed protection module is used to build an installation and fixing bracket with biocompatible materials, attach the electronic components to the endotracheal intubation tube wall, and provide a locking function to prevent falling off or deviation;

[0016] The integrated display module is used to obtain the real-time temperature and humidity data collected by the detection sensor module and display the values of the real-time temperature and humidity data through an external display;

[0017] The power supply module is used to provide an independent power supply, monitor the battery power of the power supply in real time, display it using the integrated display module, and can be connected to a power line for continuous power supply;

[0018] The external interface module is used to provide wireless communication components and connection interfaces with the device control terminal, and support data transmission and control signal exchange.

[0019] Furthermore, the device control terminal includes: a communication interface module, a data processing module, an initial setting module, a temperature and humidity prediction module, an abnormal warning module, and a control and adjustment module;

[0020] Among them, the communication interface module is used to provide a data communication and signal exchange channel between the airway monitoring terminal and the medical monitoring station, obtain the real-time temperature and humidity data collected by the airway monitoring terminal, and upload the data analysis result and the control signal to the medical monitoring station;

[0021] The data processing module is used to preprocess the real-time temperature and humidity data;

[0022] The initial setting module is used to manually or automatically select different control modes based on the pre-input patient identity information, and set the temperature and humidity thresholds that meet the personalized needs of the patient;

[0023] The temperature and humidity prediction module is used to predict the temperature and humidity change trend inside the endotracheal tube in the future time period according to the recorded historical temperature and humidity data, combined with the patient's physiological signs and environmental data;

[0024] The abnormal warning module is used to monitor the real-time temperature and humidity data and the temperature and humidity prediction data based on the temperature and humidity thresholds, analyze potential abnormal phenomena, and provide multi-level intelligent warning reminders;

[0025] The control and adjustment module is used to calculate the control parameters of the airway temperature and humidity adjustment device in the future time period according to the prediction result and the abnormal analysis result of the real-time temperature and humidity data, and perform personalized dynamic optimization on the control parameters based on the environmental data, the patient's physiological signs, and the error between the real-time temperature and humidity data and the target data, so as to control the temperature and humidity values inside the endotracheal tube in the future time period.

[0026] Furthermore, the initial setting module includes: an information input unit, a mode selection unit, a threshold setting unit, a learning and optimization unit, and an interactive operation unit;

[0027] Among them, the information input unit is used to input the patient identity information and physiological signs, and match them in the historical archive. If there is a historical archive of the patient, the historical control mode and temperature and humidity thresholds are selected. If there is no historical archive of the patient, the manual or automatic control mode is selected for the first time;

[0028] The mode selection unit is used to select the corresponding control mode according to the patient identity information and physiological signs. When in the manual mode, the temperature and humidity threshold range is manually input. When in the automatic mode, the historical archive most similar to the patient identity information and physiological signs is matched in the historical archive, and the corresponding temperature and humidity threshold range is selected and set;

[0029] A learning and optimization unit is used to continuously record the historical temperature and humidity data and feedback information during the patient's usage, store them in the historical archive, model the patient's temperature and humidity requirements through machine learning, and adjust the temperature and humidity thresholds according to the historical temperature and humidity data, feedback information, and real-time temperature and humidity data;

[0030] An interaction operation unit is used to provide an intuitive operation interface, supporting functions such as information input, control mode selection, and display and adjustment of temperature and humidity thresholds.

[0031] Furthermore, the temperature and humidity prediction module includes: a variable setting unit, a model establishment unit, a training and optimization unit, and a model prediction unit;

[0032] Among them, the variable setting unit is used to set the input variables of the temperature and humidity prediction model, normalize the input variables using the min-max normalization method, and divide them into a training set and a test set. The input variables include historical temperature and humidity data, physiological signs, and environmental data;

[0033] The model establishment unit is used to create a backpropagation neural network including an input layer, a hidden layer, and an output layer, calculate the number of nodes in the hidden layer using the empirical formula method, and build the model architecture;

[0034] The training and optimization unit is used to combine the dung beetle optimization algorithm with the backpropagation neural network, utilize the global search ability and fast convergence ability of the dung beetle optimization algorithm to update and optimize the initial weights and thresholds of the backpropagation neural network, and construct a temperature and humidity prediction model for the combined neural network. The temperature and humidity prediction model includes a humidity prediction model and a temperature prediction model;

[0035] The model prediction unit is used to set the prediction period for temperature and humidity prediction, input the real-time temperature and humidity data, environmental data, and physiological signs at the current moment into the temperature and humidity prediction model, predict the temperature and humidity prediction data in the future time period, and draw the change curve of temperature and humidity data over time.

[0036] Furthermore, combining the dung beetle optimization algorithm with the backpropagation neural network, and using the global search ability and fast convergence ability of the dung beetle optimization algorithm to update and optimize the initial weights and thresholds of the backpropagation neural network, the construction of the temperature and humidity prediction model for the combined neural network includes:

[0037] Initialize the structural parameters of the dung beetle algorithm and the backpropagation neural network, obtain the standardized data after normalizing the historical temperature and humidity data, physiological signs, and environmental data. Each dung beetle represents a solution vector of weights and thresholds, and each solution vector contains the weights and biases of all layers of the backpropagation neural network;

[0038] When the dung beetle rolls the ball forward without obstacles, update the position of the dung beetle individual after the ball rolls forward. When the dung beetle encounters an obstacle and cannot move forward, reposition by dancing and update the position of the dung beetle individual after dancing;

[0039] Adopt a boundary selection strategy to simulate the female breeding area and set the upper and lower limits of the breeding area;

[0040] Set the upper and lower limits of the foraging area. When the foraging dung beetle starts foraging, update the position of the dung beetle individual after foraging;

[0041] When the stealing dung beetle starts stealing, update the position of the dung beetle individual after stealing;

[0042] Find the best position and fitness value of the current dung beetle and determine whether the preset termination condition is reached. If it is reached, execute the next step. If not, continue to find the best position of the dung beetle;

[0043] Train the backpropagation neural network, transfer the globally optimal weights and thresholds optimized by the dung beetle optimization algorithm to the backpropagation neural network to obtain a temperature and humidity prediction model.

[0044] Furthermore, the calculation formula for updating the position of the dung beetle individual after the ball rolls forward is:

[0045] ;

[0046] In the formula, is the position information of the i th dung beetle at the t th iteration; a is the natural coefficient; k is a constant; t is the number of iterations; b is a random number; is the globally worst position.

[0047] Furthermore, the anomaly warning module includes: a data comparison unit, an anomaly detection unit, a warning generation unit, and a feedback adjustment unit;

[0048] Among them, the data comparison unit is used to compare the real-time temperature and humidity data with the upper and lower limits of the temperature and humidity threshold range. If it exceeds the temperature and humidity threshold range, it is marked as an anomaly, and the real-time temperature and humidity data is compared with the temperature and humidity prediction data to determine whether the deviation between the real-time temperature and humidity data and the temperature and humidity prediction data exceeds the set range. If it exceeds, it is marked as an anomaly;

[0049] The anomaly detection unit is used to check potential anomaly phenomena according to the comparison result of the real-time temperature and humidity data and the temperature and humidity prediction value, and determine the anomaly type and cause by using the anomaly rule engine;

[0050] An early warning generation unit is used to generate multi-level early warning information based on the abnormal detection results. The multi-level early warning information includes green early warning, yellow early warning, and red early warning. When in the green early warning, the current regulation parameters are maintained. When in the yellow early warning, the control adjustment module is used to perform automatic control adjustment. When in the red early warning, an artificial intervention warning is triggered.

[0051] A feedback adjustment unit is used to trigger corresponding temperature and humidity intervention measures according to the early warning level.

[0052] Furthermore, the control adjustment module includes: a regulation parameter calculation unit, a personalized dynamic optimization unit, a multi-variable regulation unit, and an evaluation feedback unit.

[0053] Among them, the regulation parameter calculation unit is used to set the standard target of temperature and humidity according to the current temperature and humidity threshold range, calculate the actual error between the real-time temperature and humidity data and the standard target, as well as the predicted error between the predicted temperature and humidity data and the standard target, and calculate the regulation parameters that the airway temperature and humidity adjustment device needs to maintain the temperature and humidity at the standard target through the PID control algorithm.

[0054] The personalized dynamic optimization unit is used to perform personalized optimization on the regulation parameters based on the patient's physiological signs and environmental data to adapt to the temperature and humidity requirements of different patients in different environments.

[0055] The device control output unit is used to output the optimized regulation parameters to the corresponding airway temperature and humidity adjustment device to control the operation model and operation state at future times.

[0056] The evaluation feedback unit is used to continuously monitor the operation state of the airway temperature and humidity adjustment device and the real-time temperature and humidity data in the endotracheal tube, evaluate the adjustment effect in real time. If there is an expected error in the adjustment effect, the regulation parameters are optimized through the feedback result. If there is no error in the adjustment effect, no adjustment is required.

[0057] Furthermore, performing personalized optimization on the regulation parameters based on the patient's physiological signs and environmental data to adapt to the temperature and humidity requirements of different patients in different environments includes:

[0058] Based on the patient's physiological signs, a tolerance model for the patient's tolerance to temperature and humidity changes is established. By real-time monitoring the numerical changes in the physiological signs, the current physiological state of the patient is dynamically evaluated, and the tolerance to temperature and humidity changes at the current moment is analyzed.

[0059] According to the tolerance evaluation result of the patient's physiological signs, combined with the environmental data, the temperature and humidity threshold range is optimized, the personalized temperature and humidity target is calculated, and the predicted regulation parameters at future times are optimized to control the airway temperature and humidity adjustment device to adjust the inside of the endotracheal tube to the temperature and humidity target.

[0060] Furthermore, calculating the personalized temperature and humidity targets includes the temperature value to be adjusted and the humidity value to be adjusted;

[0061] Among them, the calculation formula for the temperature value to be adjusted is:

[0062] ;

[0063] In the formula, ΔT adjust is the temperature value to be adjusted; K T is the temperature adjustment coefficient; T target is the set temperature standard target; T current is the current temperature; T normal is the patient's current body temperature;

[0064] The calculation formula for the humidity value to be adjusted is:

[0065] ;

[0066] ΔH adjust is the humidity value to be adjusted; K H is the humidity adjustment coefficient; H target is the set humidity standard target; H current is the current humidity; HumidityFactor is the humidity adjustment factor.

[0067] The beneficial effects of the present invention are as follows:

[0068] 1. By real-time monitoring of the temperature and humidity changes in the endotracheal intubation, combined with the patient's physiological signs and environmental data, it provides personalized temperature and humidity regulation and abnormal warning functions; it has intelligent data analysis and prediction capabilities, can predict future temperature and humidity trends, automatically adjust control parameters, and dynamically optimize according to the patient's signs and environmental status to ensure that the temperature and humidity are within the most suitable range, improving the patient's comfort and experience effect; through the combination of the temperature and humidity prediction module, abnormal warning module and personalized dynamic optimization control, the present invention realizes high-precision, high-stability and personalized temperature and humidity management, significantly improving the accuracy and safety of clinical treatment and nursing.

[0069] 2. By combining the dung beetle optimization algorithm with the backpropagation neural network, the advantages of the dung beetle algorithm in global search and rapid convergence are fully utilized, achieving precise optimization of the weights and thresholds of the backpropagation neural network. Thus, a temperature and humidity prediction model with high precision and high stability is constructed, which can perform personalized temperature and humidity prediction and adjustment based on the patient's physiological signs and environmental data, automatically adjust the temperature and humidity parameters, ensure that the temperature and humidity inside the tracheal intubation are maintained within the most suitable range, effectively improve the patient's comfort and experience effect, optimize the performance of the temperature and humidity prediction model, enhance the system's adaptability and prediction accuracy in complex environments, and significantly enhance the intelligence and personalization level of tracheal intubation temperature and humidity monitoring and control. BRIEF DESCRIPTION OF THE DRAWINGS

[0070] The drawings described herein are used to provide a further understanding of the present invention, form a part of the present invention, and the illustrative embodiments and descriptions thereof are used to explain the present invention and do not constitute an improper limitation of the present invention. In the drawings:

[0071] Figure 1 is a schematic block diagram of a tracheal intubation temperature and humidity monitoring and control system according to an embodiment of the present invention.

[0072] Reference numerals in the drawings: 1, airway monitoring terminal; 2, device control terminal; 3, medical monitoring station. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0073] In order to make the objectives, technical solutions and advantages of the present invention clearer, the present invention will be further described in detail below with reference to the drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0074] Please refer to Figure 1 , a tracheal intubation temperature and humidity monitoring and control system, which includes:

[0075] An airway monitoring terminal 1, which is used to be installed on the wall of the tracheal intubation, to monitor the temperature and humidity changes inside the tracheal intubation in real time, obtain real-time temperature and humidity data, and integrate data display and transmission functions to synchronously display and transmit the data information of the real-time temperature and humidity data.

[0076] In the description of the present invention, the airway monitoring terminal 1 includes: a waterproof coating module (not shown in the figure), a detection sensor module (not shown in the figure), a fixed protection module (not shown in the figure), an integrated display module (not shown in the figure), a power supply module (not shown in the figure), and an external interface module (not shown in the figure).

[0077] The waterproof coating module is used to protect the electronic components from moisture and liquid damage and maintain the long-term stable operation of the electronic components in the humid environment inside the tracheal intubation.

[0078] Specifically, the airway monitoring terminal 1 will be directly exposed inside the airway and tracheal intubation and will come into contact with moist gases (such as oxygen, humidified air, etc.). Therefore, waterproofing is crucial. The waterproof coating module can effectively protect the sensors and circuits from moisture and liquids, ensuring the long-term stable operation of the device in a humid environment. Coating materials with good breathability and waterproofness need to be selected to ensure the safety of internal electronic components without affecting the working accuracy of the temperature and humidity sensors. At the same time, precise sealing technology is adopted to ensure the waterproof performance of connection points and interfaces, preventing the external environment from damaging the sensors and circuit boards.

[0079] The detection sensor module is used to integrate a temperature sensor and a humidity sensor to continuously monitor the temperature and humidity status and changes inside the tracheal intubation, obtaining real-time temperature and humidity data.

[0080] Specifically, the temperature sensor is used to continuously monitor the air temperature inside the tracheal intubation. Common types of temperature sensors include thermistors, thermocouples, etc. When selecting a sensor, its response time, accuracy, and stability need to be considered. The humidity sensor is used to monitor the air humidity inside the tracheal intubation. Humidity sensors usually use capacitive, resistive, or electronic sensors. When selecting, attention should be paid to its measurement range, accuracy, and anti-interference ability.

[0081] The fixed protection module is used to build an installation and fixation bracket using biocompatible materials, attach the electronic components to the wall of the tracheal intubation, and provide a locking function to prevent detachment or displacement.

[0082] Specifically, the fixed protection module is used to fix and protect the airway monitoring terminal, firmly install it inside the tracheal intubation, and avoid the displacement or damage of the device position caused by the patient's activities or external factors. The fixed protection module can ensure the stability of the monitoring terminal inside the tracheal intubation and guarantee the data accuracy during long-term use.

[0083] The integrated display module is used to obtain the real-time temperature and humidity data collected by the detection sensor module and display the numerical values of the real-time temperature and humidity data through an external display.

[0084] The power supply module is used to provide an independent power supply, continuously monitor the battery power of the power supply, display it using the integrated display module, and can be connected to a power line for continuous power supply.

[0085] Specifically, it provides the power required for the airway monitoring terminal 1 to ensure the continuous operation of the device. The power module needs to have the characteristics of high efficiency and long battery life, especially in the ward environment, reducing the maintenance frequency of medical equipment. A high-performance, long-life rechargeable battery (such as a lithium battery) needs to be selected to provide power for the device. The battery should have a large capacity to extend the usage cycle.

[0086] An external interface module for providing a wireless communication component and a connection interface with the device control terminal 2, supporting data transmission and control signal exchange.

[0087] The device control terminal 2 is used to establish a communication connection with the trachea monitoring terminal and the medical monitoring station, obtain the collected real-time temperature and humidity data, judge whether there is an abnormal temperature and humidity in the tracheal intubation through data analysis, trigger an airway temperature and humidity abnormal warning according to the judgment result, and control the airway temperature and humidity regulation.

[0088] In the description of the present invention, the device control terminal 2 includes: a communication interface module (not shown in the figure), a data processing module (not shown in the figure), an initial setting module (not shown in the figure), a temperature and humidity prediction module (not shown in the figure), an abnormal warning module (not shown in the figure), and a control and regulation module (not shown in the figure).

[0089] In addition, in the device control terminal 2, the communication interface module, the data processing module, the initial setting module, the temperature and humidity prediction module, the abnormal warning module, and the control and regulation module are connected in sequence.

[0090] The communication interface module is used to provide a data communication and signal exchange channel with the airway monitoring terminal 1 and the medical monitoring station 3, obtain the real-time temperature and humidity data collected by the airway monitoring terminal 1, and upload the data analysis result and the control signal to the medical monitoring station 3.

[0091] Specifically, the communication interface module is responsible for data communication and signal exchange between the device control terminal 2, the airway monitoring terminal 1, the medical monitoring station 3, and other related devices. Through this module, the device control terminal can receive real-time data from the airway monitoring terminal, and at the same time, can also feedback the processing result to other systems (such as the medical monitoring station) or control the airway temperature and humidity regulation device.

[0092] The data processing module is used to preprocess the real-time temperature and humidity data.

[0093] Specifically, the data processing module is responsible for real-time processing of the temperature and humidity data received from the airway monitoring terminal 1, including data cleaning, denoising, smoothing processing, etc. The data processing module provides high-quality input data for subsequent analysis and decision-making, and dynamically adjusts the control strategy according to the actual needs of the patient. Remove the influence factors such as sensor error and signal interference, ensure the accuracy of the data, convert the original temperature and humidity data into a form convenient for analysis, and perform data preprocessing and storage.

[0094] The initial setting module is used to manually or automatically select different control modes based on the pre-input patient identity information and set the temperature and humidity thresholds that meet the personalized needs of the patient.

[0095] In the description of the present invention, the initial setting module includes: an information input unit (not shown in the figure), a mode selection unit (not shown in the figure), a threshold setting unit (not shown in the figure), a learning and optimization unit (not shown in the figure), and an interaction operation unit (not shown in the figure).

[0096] In addition, in the initial setting module, the information input unit, the mode selection unit, the threshold setting unit, the learning and optimization unit, and the interaction operation unit are sequentially connected.

[0097] The information input unit is used to input the patient's identity information and physiological signs, match them in the historical archive, if there is a historical archive of the patient, select the historical control mode and temperature and humidity threshold, if there is no historical archive of the patient, select the manual or automatic control mode for the first time.

[0098] The mode selection unit is used to select the corresponding control mode according to the patient's identity information and physiological signs. When in the manual mode, input the temperature and humidity threshold range manually. When in the automatic mode, match the historical archive most similar to the patient's identity information and physiological signs in the historical archive, and select and set the corresponding temperature and humidity threshold range of the historical archive.

[0099] Specifically, the control mode refers to different temperature and humidity setting schemes to meet the needs of different types of patients. According to the patient's personal information and clinical needs, the mode setting module should provide two options.

[0100] Automatic mode selection: In this mode, the system automatically selects a suitable temperature and humidity control mode according to the patient's basic information (such as age, weight, disease type, etc.). Through a pre-established database or model, this mode can recommend the optimal temperature and humidity threshold and control strategy for different patient groups. Establish a temperature and humidity control data model corresponding to different patient groups (such as children, adults, the elderly, critically ill patients, etc.) in the mode setting module. For example, children may need higher humidity to prevent airway dryness, while the elderly may be more sensitive to temperature changes. Based on the patient's specific characteristics, the system will select a suitable temperature and humidity control mode from the database and automatically set the temperature and humidity threshold (such as temperature range, humidity range). This automatic selection process can be continuously optimized through data mining or machine learning algorithms, enabling the system to adjust the control strategy in real time.

[0101] Manual mode selection: For patients who require personalized adjustment, medical staff can manually select the mode and enter the specific temperature and humidity range suitable for the patient. For example, for certain specific diseases (such as COPD patients), a lower temperature and higher humidity may be required, while for other types of respiratory failure patients, a higher temperature and moderate humidity may be needed. The manual mode selection interface allows medical staff to input or select specific control modes through a user-friendly interface (such as a touch screen, PC, or mobile device). The interface should provide different preset modes (such as "child mode", "adult mode", "critical care mode", etc.) and allow adjustment of the temperature and humidity settings in the mode. Custom settings allow doctors or nurses to input personalized temperature and humidity ranges based on the patient's real-time physiological status, and the system will generate real-time control strategies based on these inputs.

[0102] In addition, the threshold settings are based on age and weight. Patients of different ages and weights have different requirements for temperature and humidity. For example, children's respiratory tracts are more vulnerable and usually require higher humidity; while the elderly may be intolerant to excessive humidity. The type of disease also needs to be considered. For example, patients with chronic obstructive pulmonary disease (COPD) usually require low-temperature and humid air to relieve respiratory irritation; patients with acute respiratory failure may require higher temperature and humidity to help reduce airway discomfort and increase oxygen inhalation. In addition, the influence of environmental data also needs to be considered. The indoor temperature and humidity environment also needs to be taken into account. For example, if the indoor air is dry, the humidity output of the humidifier may need to be increased.

[0103] The learning and optimization unit is used to continuously record the historical temperature and humidity data and feedback information during the patient's use, store them in the historical archive, model the patient's temperature and humidity requirements through machine learning, and adjust the temperature and humidity thresholds according to the historical temperature and humidity data, feedback information, and real-time temperature and humidity data.

[0104] Specifically, by continuously monitoring the patient's physiological data (such as body temperature, respiratory rate, etc.), the temperature and humidity thresholds can be dynamically adjusted according to real-time feedback. If it is found that the patient's body temperature is too low or too high, the system can automatically adjust the temperature and humidity settings to avoid discomfort caused by inappropriate temperature and humidity for the patient.

[0105] The learning and optimization unit can model the temperature and humidity requirements of each patient through machine learning (such as a regression model based on neural networks), and gradually optimize the temperature and humidity control thresholds according to the patient's historical data, feedback information, and real-time monitoring data.

[0106] The interaction operation unit is used to provide an intuitive operation interface, supporting functions such as information input, control mode selection, and display and adjustment of temperature and humidity thresholds.

[0107] A temperature and humidity prediction module, which is used to predict the changing trend of the temperature and humidity inside the endotracheal tube in a future time period according to the recorded historical temperature and humidity data, combined with the patient's physiological signs and environmental data.

[0108] In the description of the present invention, the temperature and humidity prediction module includes: a variable setting unit (not shown in the figure), a model establishment unit (not shown in the figure), a training and optimization unit (not shown in the figure), and a model prediction unit (not shown in the figure).

[0109] In addition, in the temperature and humidity prediction module, the variable setting unit, the model establishment unit, the training and optimization unit, and the model prediction unit are sequentially connected.

[0110] The variable setting unit is used to set the input variables of the temperature and humidity prediction model, normalize the input variables by using the min-max normalization method, and divide them into a training set and a test set. The input variables include historical temperature and humidity data, physiological signs, and environmental data.

[0111] The model establishment unit is used to create a backpropagation neural network including an input layer, a hidden layer, and an output layer, calculate the number of nodes in the hidden layer by using an empirical formula method, and build a model architecture.

[0112] The training and optimization unit is used to combine the dung beetle optimization algorithm with the backpropagation neural network, utilize the global search ability and fast convergence ability of the dung beetle optimization algorithm to update and optimize the initial weights and thresholds of the backpropagation neural network, and construct a temperature and humidity prediction model of the combined neural network. The temperature and humidity prediction model includes a humidity prediction model and a temperature prediction model.

[0113] Specifically, the Dung beetle optimizer (DBO) simulates the behaviors of dung beetles such as rolling balls, dancing, foraging, stealing, and reproducing. It is a heuristic global optimization algorithm that simulates the behaviors of dung beetles (scarab beetles) such as rolling balls, dancing, foraging, stealing, and reproducing. The DBO algorithm takes into account both exploration ability and exploitation ability, has fast convergence, high accuracy, and strong stability.

[0114] The dung beetle quickly rolls the dung ball backward, which can prevent competition with other dung beetles. The ball-rolling behavior uses celestial cues (sunlight, moon, polarized light) for navigation. Specifically, it uses light sources to roll the ball in a straight line. If there is no light and it is completely dark, the ball-rolling path is curved; other natural factors may cause the dung beetle's ball-rolling path to deviate from the original direction, such as wind speed, ground flatness, etc.; when encountering an obstacle, it may stop rolling and not move forward or be unable to move forward. The dung beetle may dance (rotate, pause, etc.) on the dung ball and then decide in which direction to move; the purpose of the dung beetle rolling the ball is on the one hand to lay eggs and reproduce the next generation, and on the other hand to provide food for the larvae; therefore, the dung ball is very important to the dung beetle.

[0115] The behaviors of dung beetles include ball-rolling behavior, dancing behavior, reproductive behavior, foraging behavior, and stealing behavior.

[0116] 1. Dung beetle ball-rolling behavior: Dung beetles use celestial cues for navigation to make the dung ball move in a straight line along a specified direction. To simulate the ball-rolling behavior, the dung beetle moves along a given direction in the search domain. Considering sunlight navigation, the intensity of sunlight affects the ball-rolling path of the dung beetle.

[0117] 2. Dung beetle dancing behavior: When a dung beetle encounters an obstacle, it dances to reposition itself and obtain a new route. Dancing is very important for ball-rolling dung beetles. To imitate the dancing behavior, using the tangent function value on [0, p i , the dung beetle determines a new direction to roll the ball backward.

[0118] 3. Dung beetle reproductive behavior: Dung beetles roll the dung ball to a safe place and hide it, select an egg-laying point, and use the boundary selection strategy to simulate the egg-laying area of female dung beetles.

[0119] 4. Dung beetle foraging behavior: Adult small dung beetles (foraging dung beetles) will climb out to look for food. The established foraging area guides the small dung beetles to forage. First, define the boundary of the optimal foraging area.

[0120] 5. Dung beetle stealing behavior: Some dung beetles will steal the dung balls of other dung beetles, and they are called thief dung beetles or stealing dung beetles.

[0121] In the description of the present invention, the dung beetle optimization algorithm is combined with the backpropagation neural network. Utilizing the global search ability and fast convergence ability of the dung beetle optimization algorithm, the initial weights and thresholds of the backpropagation neural network are updated and optimized. The construction of the temperature and humidity prediction model of the combined neural network includes:

[0122] Step S201: Initialize the structural parameters of the dung beetle algorithm and the backpropagation neural network, and obtain the normalized standardized data of historical temperature and humidity data, physiological signs, and environmental data. Each dung beetle represents a solution vector of weights and thresholds, and each solution vector contains the weights and biases of all layers of the backpropagation neural network.

[0123] Step S202: When the dung beetle rolls the ball forward without obstacles, update the position of the dung beetle individual after rolling the ball forward. When the dung beetle encounters an obstacle and cannot move forward, reposition itself by dancing and update the position of the dung beetle individual after dancing.

[0124] In the description of the present invention, the calculation formula for updating the position of the dung beetle individual after rolling the ball forward is:

[0125] ;

[0126] In the formula, is the position information of the i th dung beetle at the t th iteration;a is a natural coefficient; k is a constant; t is the number of iterations; b is a random number; is the global worst position.

[0127] Step S203: Simulate the female breeding area using the boundary selection strategy and set the upper and lower limits of the breeding area.

[0128] Step S204: Set the upper and lower limits of the foraging area. When the foraging dung beetle starts foraging, update the position of the dung beetle individual after foraging.

[0129] Step S205: When the stealing dung beetle starts stealing, update the position of the dung beetle individual after stealing.

[0130] Step S206: Find the best position and fitness value of the current dung beetle, and determine whether the preset termination condition is reached. If it is reached, execute the next step. If not, continue to find the best position of the dung beetle and repeat steps S202 - S206.

[0131] Step S207: Train the backpropagation neural network, transfer the globally optimal weights and thresholds optimized by the dung beetle optimization algorithm to the backpropagation neural network to obtain the temperature and humidity prediction model.

[0132] The model prediction unit is used to set the prediction period of the temperature and humidity prediction, input the real - time temperature and humidity data, environmental data and physiological signs at the current moment into the temperature and humidity prediction model, predict the temperature and humidity prediction data in the future time period, and draw the change curve of the temperature and humidity data over time.

[0133] The abnormal warning module is used to monitor the real - time temperature and humidity data and the temperature and humidity prediction data based on the temperature and humidity thresholds, analyze potential abnormal phenomena, and provide multi - level intelligent warning reminders.

[0134] In the description of the present invention, the abnormal warning module includes: a data comparison unit (not shown in the figure), an abnormal detection unit (not shown in the figure), a warning generation unit (not shown in the figure), and a feedback adjustment unit (not shown in the figure).

[0135] In addition, in the abnormal warning module, the data comparison unit, the abnormal detection unit, the warning generation unit, and the feedback adjustment unit are sequentially connected.

[0136] The data comparison unit is used to compare the real - time temperature and humidity data with the upper and lower limits of the temperature and humidity threshold range. If it exceeds the temperature and humidity threshold range, it is marked as abnormal, and the real - time temperature and humidity data are compared with the temperature and humidity prediction data to determine whether the deviation between the real - time temperature and humidity data and the temperature and humidity prediction data exceeds the set range. If it exceeds, it is marked as abnormal.

[0137] Anomaly detection unit, which is used to check potential abnormal phenomena according to the comparison result between real-time temperature and humidity data and predicted temperature and humidity values, and determine the type and cause of the anomaly by using an anomaly rule engine.

[0138] Specifically, according to the comparison between the threshold comparison result and the predicted data, it is detected whether there are potential abnormal phenomena. Common types of anomalies include: too high or too low temperature, too high or too low humidity, sudden change in temperature and humidity, too large fluctuation in temperature and humidity, etc. The anomaly rule engine can detect anomalies based on set rules (such as exceeding the standard of temperature and humidity, too large fluctuation, etc.). For example, if the real-time data continuously exceeds the threshold for a certain period of time, it is determined as an anomaly; if the deviation between the real-time data and the predicted data exceeds the set error range, an anomaly warning is triggered.

[0139] By comparing with preset thresholds and historical data, it is checked whether the current temperature and humidity data is abnormal. For example, assuming that the set temperature threshold is [36.0°C, 37.5°C], if the real-time data is 38.0°C, a temperature exceeding the standard warning is triggered. The future data output by the temperature and humidity prediction model is compared with the real-time data to analyze the degree to which the current data deviates from the predicted value. For example, if the real-time temperature is 38.0°C and the predicted temperature is 36.5°C, the deviation is 1.5°C. If it exceeds the set allowable deviation range, a warning is triggered.

[0140] Warning generation unit, which is used to generate multi-level warning information based on the anomaly detection result. The multi-level warning information includes green warning, yellow warning and red warning. When in the green warning, the current control parameters are maintained. When in the yellow warning, the control adjustment module is used to execute automatic control adjustment. When in the red warning, a manual intervention warning is triggered.

[0141] Feedback adjustment unit, which is used to trigger corresponding temperature and humidity intervention measures according to the warning level.

[0142] Control adjustment module, which is used to calculate the control parameters of the airway temperature and humidity adjustment device in the future time period according to the prediction result of the real-time temperature and humidity data and the anomaly analysis result, and perform personalized dynamic optimization on the control parameters based on the environmental data, patient physiological signs, and the error between the real-time temperature and humidity data and the target data, so as to regulate the temperature and humidity values in the endotracheal tube in the future time period.

[0143] In the description of the present invention, the control adjustment module includes: a control parameter calculation unit (not shown in the figure), a personalized dynamic optimization unit (not shown in the figure), a multivariable control unit (not shown in the figure), and an evaluation feedback unit (not shown in the figure).

[0144] In addition, in the control and regulation module, the regulation parameter calculation unit, the personalized dynamic optimization unit, the multivariable regulation unit, and the evaluation and feedback unit are sequentially connected.

[0145] The regulation parameter calculation unit is used to set the standard targets for temperature and humidity according to the current temperature and humidity threshold range, calculate the actual error between the real-time temperature and humidity data and the standard targets, as well as the predicted error between the predicted temperature and humidity data and the standard targets, and calculate the regulation parameters required for the airway temperature and humidity adjustment device to maintain the temperature and humidity at the standard targets through the PID control algorithm.

[0146] The personalized dynamic optimization unit is used to perform personalized optimization on the regulation parameters based on the patient's physiological signs and environmental data to adapt to the temperature and humidity requirements of different patients in different environments.

[0147] In the description of the present invention, performing personalized optimization on the regulation parameters based on the patient's physiological signs and environmental data to adapt to the temperature and humidity requirements of different patients in different environments includes:

[0148] Step S211: Based on the patient's physiological signs, establish a tolerance model for evaluating the patient's tolerance to temperature and humidity changes. By real-time monitoring the numerical changes in the physiological signs, dynamically evaluate the patient's current physiological state and analyze the tolerance to temperature and humidity changes at the current moment.

[0149] Specifically, the patient's physiological signs include: age (Age), weight (Weight), basic disease conditions (such as respiratory diseases, heart diseases, etc.), current body temperature (Body Temperature), respiratory rate (Respiratory Rate), heart rate (Heart Rate), and so on.

[0150] Perform a preliminary analysis of the patient's physiological data to evaluate the patient's tolerance. For example, patients with heavier weights or chronic diseases may have lower tolerance to temperature and humidity changes and thus require slower adjustment. A tolerance model can be designed, for example: Tolerance = f ( Age , Weight , Diseases ), which is used to calculate the overall tolerance of the patient based on age, weight, and disease conditions. A tolerance coefficient can be assigned to different patients (for example, 0.8 indicates lower tolerance and 1.2 indicates higher tolerance).

[0151] Step S212: According to the tolerance evaluation results of the patient's physiological signs, combined with the environmental data, optimize the temperature and humidity threshold range, calculate the personalized temperature and humidity targets, and optimize the predicted regulation parameters for future moments to control the airway temperature and humidity adjustment device to adjust the inside of the tracheal intubation to the temperature and humidity targets.

[0152] Specifically, by continuously monitoring physiological sign data (such as body temperature, heart rate, respiratory rate, etc.), the current physiological state of the patient is dynamically evaluated to determine their tolerance to changes in temperature and humidity. Based on the monitored physiological sign data, the current physiological condition of the patient is evaluated. For example, when the body temperature is too high or too low, the power output of the temperature and humidity regulation device needs to be adjusted; when the heart rate is too fast or too slow, it may indicate that the patient is in a high-stress state, and the rate of change in temperature and humidity also needs to be adjusted.

[0153] Therefore, personalized temperature and humidity target ranges can be set according to the patient's physiological data and environmental conditions, and the control parameters of the temperature and humidity regulation device can be optimized. The target temperature and humidity can be achieved by adjusting the output power of the airway temperature and humidity regulation device. When the temperature is too high, the regulation device should reduce the heating power and increase the humidification output of the humidity control device; when the temperature is too low, the adjustment should be reversed.

[0154] In the description of the present invention, calculating the personalized temperature and humidity target includes the temperature value to be adjusted and the humidity value to be adjusted.

[0155] Among them, the calculation formula for the temperature value to be adjusted is:

[0156] ;

[0157] In the formula, ΔT adjust is the temperature value to be adjusted; K T is the temperature adjustment coefficient; T target is the set standard temperature target; T current is the current temperature; T normal is the patient's current body temperature;

[0158] The calculation formula for the humidity value to be adjusted is:

[0159] ;

[0160] ΔH adjust is the humidity value to be adjusted; K H is the humidity adjustment coefficient; H target is the set standard humidity target; H current is the current humidity; HumidityFactor is the humidity adjustment factor.

[0161] The device control output unit is used to output the optimized regulation parameters to the corresponding airway temperature and humidity regulation device, and control the operation model and operation state at the future moment.

[0162] Specifically, the main task of the device control output unit is to transfer the optimized regulation parameters to the airway temperature and humidity regulation device, and control the operation mode and state of the device at the future moment. The optimized regulation parameters are calculated based on real-time data, prediction data, and personalized optimization results. By regulating the output power of the temperature and humidity regulation device, the working state of the heater or humidifier, etc., it is ensured that the temperature and humidity in the endotracheal tube always remain within the set optimal range.

[0163] In the device control output unit, the optimized regulation parameters are transmitted to the airway temperature and humidity regulation device through the communication interface, and the device will adjust its operation state according to these parameters. For example, if the regulation result requires increasing the output power of the humidifier, the system will inform the humidifier to increase the output through the control signal, thereby increasing the humidity; if the temperature is too high, the control signal will adjust the power of the heater to lower the temperature.

[0164] The evaluation and feedback unit is used to continuously monitor the operation state of the airway temperature and humidity regulation device and the real-time temperature and humidity data in the endotracheal tube, evaluate the regulation effect in real time. If there is an expected error in the regulation effect, the regulation parameters are optimized through the feedback result; if there is no error in the regulation effect, no adjustment is required.

[0165] Specifically, this unit continuously monitors the operation state of the airway temperature and humidity regulation device and the real-time temperature and humidity data in the endotracheal tube, evaluates the regulation effect in real time, and ensures that the error during the regulation process is controlled within a reasonable range. If it is found that the regulation effect does not match the expectation, the evaluation and feedback unit will optimize the regulation parameters according to the error between the real-time data and the target data through the feedback mechanism, ensuring that the system always maintains within the most suitable temperature and humidity range.

[0166] The medical monitoring station 3 is used to establish a communication connection with the device control terminal 2, obtain the monitoring data and operation states of all airway monitoring terminals 1 and device control terminals 2 within the monitoring area, display them in real time through the visualization device, and centrally store and manage the monitoring data.

[0167] Specifically, the Medical Monitoring Station (MMS) plays a core role in centralized management, data display, and monitoring in the endotracheal tube temperature and humidity monitoring control system. Specifically, it is mainly responsible for establishing a communication connection with the device control terminal, obtaining and displaying the monitoring data and operation states of all airway monitoring terminals and device control terminals within the monitoring area, ensuring that medical staff can grasp the temperature and humidity status of patients in real time and adjust the treatment plan in a timely manner.

[0168] After receiving the monitoring data from the device control terminal, the medical monitoring station centrally stores and manages this data. Historical data, real-time data, warning information, etc. will all be stored in a local or cloud database for subsequent analysis and query. The data storage uses relational databases (such as MySQL, PostgreSQL) or non-relational databases (such as MongoDB), and is optimized and configured according to the data volume, query requirements, and storage method. To ensure the security and reliability of the data, hybrid storage combining cloud storage and local storage can be used to ensure that the data is not lost.

[0169] In summary, by means of the above technical solutions of the present invention, by real-time monitoring the temperature and humidity changes inside the tracheal intubation, combining the patient's physiological signs and environmental data, personalized temperature and humidity regulation and abnormal warning functions are provided; it has intelligent data analysis and prediction capabilities, can predict future temperature and humidity trends, automatically adjust the control parameters, and perform dynamic optimization according to the patient's signs and environmental status to ensure that the temperature and humidity are within the most suitable range, improving the patient's comfort and experience effect; the present invention combines the temperature and humidity prediction module, the abnormal warning module and personalized dynamic optimization control to achieve high-precision, high-stability and personalized temperature and humidity management, significantly improving the accuracy and safety of clinical treatment and nursing. By combining the dung beetle optimization algorithm and the backpropagation neural network, giving full play to the advantages of the dung beetle algorithm in global search and fast convergence, the weights and thresholds of the backpropagation neural network are accurately optimized, thus constructing a high-precision, high-stability temperature and humidity prediction model, which can perform personalized temperature and humidity prediction and regulation based on the patient's physiological signs and environmental data, automatically adjust the temperature and humidity parameters, ensure that the temperature and humidity inside the tracheal intubation are maintained within the most suitable range, effectively improve the patient's comfort and experience effect, optimize the performance of the temperature and humidity prediction model, enhance the adaptability and prediction accuracy of the system in a complex environment, and significantly enhance the intelligence and personalization level of tracheal intubation temperature and humidity monitoring and control.

[0170] It should be understood that although the steps in the flowchart of the accompanying drawings are shown sequentially according to the indication of the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless there is a clear indication in this article, the execution of these steps has no strict order limit, and they can be executed in other orders. Moreover, at least a part of the steps in the flowchart of the accompanying drawings may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily executed at the same time, but can be executed at different times, and their execution order is not necessarily sequential, but can be executed alternately or alternately with at least a part of other steps or sub-steps or stages of other steps.

Claims

1. A tracheal intubation temperature and humidity monitoring and control system, characterized in that: include: Airway monitoring terminal; The equipment control terminal is used to establish a communication connection with the tracheal monitoring terminal and the medical monitoring station, obtain the collected real-time temperature and humidity data, and judge whether there is abnormal temperature and humidity in the tracheal tube through data analysis. According to the judgment result, the airway temperature and humidity abnormality warning is triggered and the airway temperature and humidity adjustment is controlled; Medical monitoring stations; The device control terminal comprises: The temperature and humidity prediction module is used to predict the temperature and humidity change trend inside the endotracheal tube in the future time period based on the recorded historical temperature and humidity data combined with the patient's physiological signs and environmental data; A control and adjustment module is used to calculate the control parameters of the airway temperature and humidity control device in the future time period based on the prediction results and abnormal analysis results of the real-time temperature and humidity data, and to perform personalized dynamic optimization of the control parameters based on environmental data, patient physiological signs, and the error between the real-time temperature and humidity data and the target data, so as to adjust the temperature and humidity values ​​in the endotracheal tube in the future time period; The control and regulation module comprises: The personalized dynamic optimization unit is used to optimize the control parameters based on the patient's physiological signs and environmental data to meet the temperature and humidity requirements of different patients in different environments, including: Based on the patient's physiological signs, a model for evaluating the patient's tolerance to temperature and humidity changes is established. By real-time monitoring of the numerical changes in physiological signs, the patient's current physiological state is dynamically evaluated and the patient's tolerance to temperature and humidity changes at the current moment is analyzed. Based on the tolerance assessment results of the patient's physiological signs and combined with environmental data, the temperature and humidity threshold range is optimized, the personalized temperature and humidity targets are calculated, and the control parameters predicted at future moments are optimized to control the airway temperature and humidity adjustment equipment to adjust the inside of the endotracheal tube to the temperature and humidity targets; The calculated personalized temperature and humidity targets include a temperature value to be adjusted and a humidity value to be adjusted; The calculation formula for the temperature value to be adjusted is: ； In the formula, ΔT adjust To adjust the temperature value; K T is the temperature adjustment factor; T target To set the temperature standard target; T current is the current temperature; T normal is the patient's current body temperature; The calculation formula for the humidity value to be adjusted is: ； ΔH adjust To adjust the humidity value; K H is the humidity adjustment factor; H target To set the humidity standard target; H current is the current humidity; HumidityFactor is the humidity adjustment factor.

2. A tracheal intubation temperature and humidity monitoring and control system according to claim 1, characterized in that: The airway monitoring terminal comprises: Waterproof coating module, used to protect electronic components from moisture and liquid damage, and maintain long-term stable operation of electronic components in the humid environment of the endotracheal tube; The detection sensor module is used to integrate the temperature sensor and the humidity sensor to monitor the temperature and humidity status and changes inside the endotracheal tube in real time and obtain real-time temperature and humidity data; A fixed protection module is used to construct and install a fixed bracket using biocompatible materials, attach the electronic components to the wall of the endotracheal tube, and provide a locking function to prevent falling off or deviation; An integrated display module is used to obtain the real-time temperature and humidity data collected by the detection sensor module and display the values ​​of the real-time temperature and humidity data through an external display; The power supply module is used to provide an independent power supply, monitor the battery power of the power supply in real time, display it using the integrated display module, and can be connected to the power line for continuous power supply; The external interface module is used to provide wireless communication components and a connection interface with the device control terminal, supporting data transmission and control signal exchange.

3. A tracheal intubation temperature and humidity monitoring and control system according to claim 1, characterized in that: The device control terminal also includes: The communication interface module is used to provide data communication and signal exchange channels with the airway monitoring terminal and the medical monitoring station, obtain the real-time temperature and humidity data collected by the airway monitoring terminal, and upload the data analysis results and control signals to the medical monitoring station; Data processing module, used for preprocessing real-time temperature and humidity data; An initial setting module is used to manually or automatically select different control modes based on the patient's identity information input in advance, and set the temperature and humidity thresholds that meet the patient's personalized needs; The abnormal warning module is used to monitor real-time temperature and humidity data and temperature and humidity forecast data based on temperature and humidity thresholds, analyze potential abnormal phenomena, and provide multi-level intelligent early warning reminders.

4. A tracheal intubation temperature and humidity monitoring and control system according to claim 3, characterized in that: The initial setting module includes: An information input unit is used to input the patient's identity information and physiological signs, and match them in the historical archive. If the patient's historical archive exists, the historical control mode and temperature and humidity thresholds are selected. If the patient's historical archive does not exist, the manual or automatic control mode is selected for the first time. A mode selection unit is used to select a corresponding control mode according to the patient's identity information and physiological signs. When in manual mode, the temperature and humidity threshold range is manually input; when in automatic mode, the historical archive that is most similar to the patient's identity information and physiological signs is matched in the historical archive library, and the temperature and humidity threshold range corresponding to the historical archive is selected and set; The learning optimization unit is used to continuously record the historical temperature and humidity data and feedback information of patients during use, store them in the historical archive, model the temperature and humidity requirements of patients through machine learning, and adjust the temperature and humidity thresholds based on the historical temperature and humidity data, feedback information and real-time temperature and humidity data; The interactive operation unit is used to provide an intuitive operation interface, supporting information input, control mode selection, and temperature and humidity threshold display and adjustment functions.

5. A tracheal intubation temperature and humidity monitoring and control system according to claim 3, characterized in that: The temperature and humidity prediction module includes: The variable setting unit is used to set the input variables of the temperature and humidity prediction model. The input variables are normalized by the minimum-maximum standard method and divided into a training set and a test set. The input variables include historical temperature and humidity data, physiological signs and environmental data. The model building unit is used to create a back propagation neural network including an input layer, a hidden layer, and an output layer, calculate the number of nodes in the hidden layer using an empirical method, and build a model architecture; A training optimization unit is used to combine the dung beetle optimization algorithm with the back propagation neural network, and use the global search ability and fast convergence ability of the dung beetle optimization algorithm to update and optimize the initial weights and thresholds of the back propagation neural network, and build a temperature and humidity prediction model of the combined neural network. The temperature and humidity prediction model includes a humidity prediction model and a temperature prediction model; The model prediction unit is used to set the prediction period of temperature and humidity prediction, input the real-time temperature and humidity data, environmental data and physiological signs at the current moment into the temperature and humidity prediction model, predict the temperature and humidity prediction data in the future time period, and draw the change curve of temperature and humidity data over time.

6. A tracheal tube temperature and humidity monitoring and control system according to claim 5, characterized in that: The method combines the dung beetle optimization algorithm with the back propagation neural network, utilizes the global search capability and fast convergence capability of the dung beetle optimization algorithm, updates and optimizes the initial weights and thresholds of the back propagation neural network, and constructs a temperature and humidity prediction model of the combined neural network, including: Initialize the structural parameters of the dung beetle algorithm and the back propagation neural network, obtain the normalized data of historical temperature and humidity data, physiological signs and environmental data, each dung beetle represents a solution vector of weights and thresholds, and each solution vector contains the weights and biases of all layers of the back propagation neural network; When the dung beetle rolls the ball forward without any obstacles, the individual position of the dung beetle after the ball is rolled forward is updated. When the dung beetle encounters an obstacle and cannot move forward, it repositions itself by dancing, and the individual position of the dung beetle after dancing is updated. A boundary selection strategy was used to simulate the female breeding area, and the upper and lower limits of the breeding area were set; Set the upper and lower limits of the foraging area, and when the foraging dung beetle starts foraging, update the individual position of the dung beetle after foraging; When the thieving dung beetle starts stealing, the individual position of the dung beetle after stealing is updated; Find the best position and fitness value of the current dung beetle, and determine whether the preset termination condition is met. If so, execute the next step. If not, continue to find the best position of the dung beetle; The back propagation neural network is trained, and the global optimal weights and thresholds optimized by the dung beetle optimization algorithm are transferred to the back propagation neural network to obtain the temperature and humidity prediction model.

7. A tracheal intubation temperature and humidity monitoring and control system according to claim 3, characterized in that: The abnormal warning module includes: A data comparison unit is used to compare the real-time temperature and humidity data with the upper and lower limits of the temperature and humidity threshold range. If the temperature and humidity threshold range is exceeded, it is marked as abnormal, and the real-time temperature and humidity data is compared with the temperature and humidity forecast data to determine whether the deviation between the real-time temperature and humidity data and the temperature and humidity forecast data exceeds the set range. If it exceeds, it is marked as abnormal; The anomaly detection unit is used to check potential anomalies and determine the type and cause of anomalies based on the comparison results of real-time temperature and humidity data with the predicted temperature and humidity values ​​using an anomaly rule engine; An early warning generation unit is used to generate multi-level early warning information based on the abnormal detection results. The multi-level early warning information includes green early warning, yellow early warning and red early warning. When in green early warning, the current control parameters are maintained. When in yellow early warning, the control and adjustment module is used to perform automatic control and adjustment. When in red early warning, a manual intervention early warning is triggered; The feedback adjustment unit is used to trigger corresponding temperature and humidity intervention measures according to the warning level.

8. The endotracheal tube temperature and humidity monitoring and control system according to claim 3, characterized in that: The control and regulation module also includes: A control parameter calculation unit is used to set a standard target for temperature and humidity according to the current temperature and humidity threshold range, calculate the actual error between the real-time temperature and humidity data and the standard target, and the predicted error between the temperature and humidity prediction data and the standard target, and calculate the control parameters required by the airway temperature and humidity control device to maintain the temperature and humidity at the standard target through a PID control algorithm; The equipment control output unit is used to output the optimized control parameters to the corresponding airway temperature and humidity control equipment to control the operation model and operation status at the future moment; The evaluation feedback unit is used to continuously monitor the operating status of the airway temperature and humidity adjustment equipment and the real-time temperature and humidity data in the endotracheal tube, and to evaluate the adjustment effect in real time. If there is an expected error in the adjustment effect, the control parameters are optimized through the feedback results. If there is no error in the adjustment effect, no adjustment is required.

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