Real-time data acquisition and analysis system for anesthesia process

Abstract

The invention discloses an anesthesia process real-time data acquisition and analysis system, which relates to the technical field of medical detection and comprises a data acquisition module, a transmission module, an analysis module, a display module and a warning module, the data acquisition module comprises various sensors and a pulse monitoring unit and is used for acquiring physiological parameters and pulse conditions of a patient in an anesthesia process; the transmission module transmits the physiological parameters and the pulse conditions which are collected in real time into the analysis module; and the analysis module analyzes the physiological parameters acquired by the patient based on a linear regression model, analyzes the pulse condition, and comprehensively analyzes and judges whether the patient is in a safe anesthesia state in the anesthesia process in combination with the physiological parameters and the pulse parameters of the patient. According to the method, anesthesia hidden dangers of a patient can be found in time through analysis, an early warning signal is provided for a doctor, the doctor can take measures in advance for adjustment, the safety of the patient is guaranteed, real-time analysis and early warning are achieved, and judgment and decision making are provided for the anesthetist.

Description

Technical Field

[0001] The present invention relates to the technical field of medical detection, and specifically to a real-time data acquisition and analysis system for the anesthesia process. Background Art

[0002] Anesthesia is a medical technique that uses drugs or other methods to temporarily make a patient lose sensation during surgery or other medical procedures to relieve pain and discomfort. Anesthesia can be divided into different types such as local anesthesia, regional anesthesia, and general anesthesia. Local anesthesia is to inject anesthetic drugs at specific parts of the body to make that part lose sensation. For example, when extracting teeth, a doctor may use local anesthesia to relieve the patient's pain. Regional anesthesia is to inject anesthetic drugs around nerves or near the spinal cord to make a certain area of the body lose sensation. Common regional anesthetics include epidural anesthesia and spinal anesthesia, which are often used in childbirth and lower limb surgeries. When a patient enters the anesthetic state, an anesthesiologist will select a suitable method to maintain anesthesia according to the type and duration of the surgery, which may include continuously administering anesthetic drugs and adjusting the drug dosage to keep the patient's anesthetic depth stable, while continuing to closely monitor various physiological parameters of the patient. During the anesthesia process, accurately monitoring the patient's physiological parameters and timely analyzing these data are crucial for ensuring the safety and effectiveness of anesthesia. Currently, data collection during the anesthesia process mainly relies on various independent monitoring devices, which often can only provide a single physiological parameter, and the analysis and processing of data are usually carried out after anesthesia, unable to achieve real-time analysis and early warning, and it is difficult to integrate data between different devices, bringing difficulties to the judgment and decision-making of anesthesiologists. In view of this, we propose a real-time data acquisition and analysis system for the anesthesia process. Summary of the Invention

[0003] To solve the above technical problems, a real-time data acquisition and analysis system for the anesthesia process is provided, and this technical solution solves the problem of the inability to achieve real-time analysis and early warning as described above.

[0004] To achieve the above object, the technical solution adopted by the present invention is: a real-time data acquisition and analysis system for the anesthesia process, including: a data acquisition module, a transmission module, an analysis module, a display module, and a warning module;

[0005] The data acquisition module includes various sensors and a pulse monitoring unit, and is used to collect the physiological parameters of the patient during the anesthesia process and the patient's pulse condition;

[0006] The transmission module transmits the real-time collected physiological parameters and pulse conditions to the analysis module;

[0007] The analysis module analyzes the physiological parameters obtained by the patient based on a linear regression model, analyzes the pulse condition, and comprehensively analyzes and judges whether the patient is in a safe anesthesia state during the anesthesia process by combining the patient's physiological parameters and pulse parameters;

[0008] The display module is used to display the results of data collection in real time for intuitive observation by physicians.

[0009] When the warning module's analysis module determines that there are anesthesia risks for the patient, it issues a warning to alert the physician to make anesthesia adjustments.

[0010] Preferably, the data collection module includes a body temperature sensor and an electromyography sensor. The body temperature sensor is used to monitor the body temperature changes of the patient. An infrared body temperature sensor is adopted to obtain the body temperature by detecting the intensity of infrared radiation emitted by the human body. The electromyography sensor collects the electrical signals generated during muscle contraction and relaxation by contacting the electrode patch with the patient's muscle, and obtains a waveform diagram reflecting the electromyographic activity through amplification and filtering processing. The pulse monitoring unit captures the pulse changes of the patient based on the sensor, and continuously monitors the frequency, intensity, and regularity of the pulse in real time to provide information on the patient's cardiovascular system status.

[0011] Preferably, the transmission module transmits the physiological parameters and pulse conditions collected in real time to the analysis module, using high-quality data lines and interfaces. When various sensors in the data collection module collect the physiological parameters of the patient and the pulse monitoring unit monitors the pulse conditions of the patient, the transmission module responds quickly, packs the data and sends it out. During the transmission process, real-time data verification and error correction processing are performed, and when data anomalies and losses are found, retransmission is immediately carried out.

[0012] Preferably, based on the obtained physiological data, the analysis module evaluates the physiological data of the patient. The evaluation formula is:

[0013] Z = β 0 + β 1 X + β 2 Y + ∈

[0014] Where Z is the evaluation value of the patient's physiological data, β 0 is the intercept, β 1 and β 2 are regression coefficients, ∈ is the error term, X is the independent variable; Y is the dependent variable. Among them, the calculation formula for the regression coefficient β 1 is:

[0015]

[0016] Where n is the number of samples, X i and Y i are the values of the independent variable and the dependent variable of the i-th sample, and are the averages of the independent variable and the dependent variable. The obtained historical data is used as a data sample for verification;

[0017] Intercept β 0 The calculation formula is as follows:

[0018]

[0019] The value of the intercept is obtained through formula calculation.

[0020] Preferably, based on the acquired pulse data, the analysis module analyzes the pulse condition, and the analysis includes the frequency and intensity of the pulse. Among them, the frequency of the pulse is the number of pulse beats detected per unit time, which is the pulse frequency; the calculation formula for the pulse intensity is: record a series of pulse amplitude values, A 1 , A 2 ……A n , and the amplitude calculation formula is:

[0021]

[0022] where is the calculated average pulse amplitude value, A i is the i-th pulse amplitude value;

[0023] Combining the amplitude value of the pulse and the frequency of the pulse, based on the analysis results of the pulse frequency and amplitude value, a comprehensive judgment is made, and the calculation is based on the weighted average formula:

[0024]

[0025] where B is the patient's pulse value obtained by comprehensive evaluation, C is the frequency of the pulse, and W i is the weight.

[0026] Preferably, combining the patient's physiological parameters and pulse parameters, a comprehensive analysis is made to judge whether the patient is in a safe anesthesia state during the anesthesia process. Among them, the evaluation formula is: F = Z + B, where F is the value of comprehensive evaluation. Based on the expert analysis method, a safe threshold range value is given, and the safe threshold range value is compared with the comprehensive evaluation value F. When it is greater than the safe threshold range, it is judged that there is an anesthesia risk, and the doctor makes timely adjustments. When it is less than the safe threshold range, it is judged that there is no anesthesia risk, and the subsequent operations are continued.

[0027] Preferably, the display module is used to display the results of data acquisition in real time, providing an intuitive observation window for the doctor. The display module uses a high-resolution display screen to clearly present the data of various physiological parameters and pulse conditions. When the data acquisition module transmits the real-time acquired patient physiological parameters and pulse conditions, the display module responds quickly, processes and displays the data, and displays it on the screen in digital form.

[0028] Preferably, the display module provides a query function for historical data. Physicians can review the patient's physiological parameters and pulse conditions at different time points. The display module can be personalized according to the physician's needs, including adjusting the display color, font size, and data refresh frequency.

[0029] Preferably, when the analysis module determines through data analysis that there are anesthesia risks for the patient, the warning module responds and issues a strong warning signal. The warning module uses multiple methods to give warnings, emitting a loud and rapid sound and light alarm, through flashing lights and sharp sounds, enabling the physician to detect abnormal situations.

[0030] Preferably, after the warning is issued, the physician makes adjustments to re-evaluate and adjust the patient's anesthesia state, and analyzes the reasons for the anesthesia risks for the patient, including improper anesthesia drug dosage, abnormal patient body reaction to anesthesia, or other unexpected situations.

[0031] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0032] By analyzing the physiological parameters and pulse conditions, the present invention can provide more accurate judgment results, helping doctors better evaluate the patient's anesthesia state. By comprehensively analyzing the physiological parameters and pulse parameters and considering the patient's overall condition, the accuracy and reliability of the judgment are improved, the risk of accidents is reduced. Through analysis, anesthesia risks for the patient can be detected in a timely manner, providing a warning signal for doctors, enabling doctors to take measures in advance for adjustment, ensuring the safety of patients, and realizing real-time analysis and warning for the judgment and decision-making of anesthesiologists. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] Figure 1 It is a framework diagram of the data acquisition and analysis system of the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0034] The following description is used to disclose the present invention so that those skilled in the art can implement the present invention. The preferred embodiments described below are only examples, and those skilled in the art can think of other obvious variations.

[0035] Refer to Figure 1 As shown, the real-time data acquisition and analysis system for the anesthesia process includes: a data acquisition module, a transmission module, an analysis module, a display module, and a warning module;

[0036] The data acquisition module includes various sensors and a pulse monitoring unit, which are used to collect the patient's physiological parameters and the patient's pulse conditions during the anesthesia process;

[0037] The transmission module transmits the real-time collected physiological parameters and pulse conditions into the analysis module;

[0038] The analysis module analyzes the patient's physiological parameters and pulse conditions based on a linear regression model, and comprehensively analyzes the patient's physiological parameters and pulse parameters to determine whether the patient is in a safe anesthesia state during anesthesia;

[0039] The display module is used to display the results of data collection in real time for the physician to observe intuitively;

[0040] When the warning module analysis module determines that the patient has anesthesia risks, it issues a warning to alert the physician and make anesthesia adjustments.

[0041] This application can comprehensively collect the physiological parameters and pulse conditions of patients during anesthesia through various sensors and pulse monitoring units, provide doctors with multi-dimensional information, and help to understand the patient's physical condition more accurately. Through real-time monitoring of physiological parameters and pulse conditions, abnormal signals can be captured in the early stage of the problem, and precious time can be gained for timely intervention and treatment. The real-time collected data is quickly transmitted to the analysis module to ensure that doctors can obtain the latest patient information in a timely manner and avoid delayed diagnosis and treatment caused by information lag. Advanced transmission technology is used to ensure the stability and accuracy of data transmission and reduce the risk of data loss and errors. The analysis of physiological parameters and pulse conditions based on the linear regression model can provide more accurate judgment results and help doctors better evaluate the patient's anesthetic state. Comprehensive analysis is performed in combination with physiological parameters and pulse parameters, and the overall condition of the patient is comprehensively considered to improve the accuracy and reliability of judgment and reduce the risk of misdiagnosis and missed diagnosis. Through analysis, the patient's anesthesia risks can be discovered in time, and early warning signals can be provided to doctors so that they can take measures in advance to make adjustments and ensure the safety of patients.

[0042] The data acquisition module includes a body temperature sensor and an electromyography sensor. The body temperature sensor is used to monitor changes in the patient's body temperature. It uses an infrared body temperature sensor to obtain body temperature conditions by detecting the intensity of infrared radiation emitted by the human body. The electromyography sensor collects electrical signals generated by muscle contraction and relaxation by bringing the electrode patch into contact with the patient's muscles, and obtains a waveform reflecting electromyography activity after amplification and filtering. The pulse monitoring unit captures changes in the patient's pulse based on the sensor, detects the frequency, intensity and regularity of the pulse in real time, and provides information on the status of the patient's cardiovascular system through continuous monitoring.

[0043] The data acquisition module of this application plays a crucial fundamental role in the entire system. It contains various advanced sensor devices internally. Among them, the body temperature sensor and the electromyogram sensor play key monitoring functions. The body temperature sensor is mainly used to closely monitor the body temperature changes of patients during anesthesia. Among various types of body temperature sensors, the infrared body temperature sensor is adopted here. This type of sensor has a unique working principle. It obtains the body temperature of patients by accurately detecting the intensity of infrared radiation emitted by the human body. The human body emits infrared radiation of different intensities at different body temperature states. The infrared body temperature sensor can sensitively capture these radiation changes and accurately obtain the body temperature value of patients through complex calculation and conversion processes. This non-contact body temperature measurement method is not only convenient and fast but also can reduce the interference to patients. Especially during anesthesia, it avoids the discomfort and risks that may be brought by contact measurement. The electromyogram sensor monitors the muscle activity of patients in an innovative way. It closely contacts the electrodes with the muscles of patients. When the muscles of patients contract and relax, specific electrical signals will be generated.

[0044] The transmission module transmits the physiological parameters and pulse conditions collected in real time to the analysis module. High-quality data lines and interfaces are used. When various sensors in the data acquisition module collect the physiological parameters of patients and the pulse monitoring unit monitors the pulse conditions of patients, the transmission module responds quickly, packs the data and sends it out. During the transmission process, real-time verification and error correction processing are carried out on the data. After detecting abnormal and lost data, it will be retransmitted immediately.

[0045] The transmission module of this application plays a key bridging role in the entire system, responsible for efficiently and accurately transmitting the physiological parameters and pulse conditions collected in real time to the analysis module. To ensure the stability and reliability of data transmission, the transmission module adopts high-quality data lines and interfaces. When various sensors in the data acquisition module, such as the body temperature sensor and the electromyogram sensor, collect rich physiological parameters of patients and the pulse monitoring unit accurately monitors the pulse conditions of patients, the transmission module can respond quickly with extremely high sensitivity. It will carefully pack these valuable data in a very short time to ensure the integrity and orderliness of the data. Then, it sends the data through a reliable transmission channel, just like an efficient messenger, delivering the information to the analysis module with certainty.

[0046] Based on the obtained physiological data, the analysis module evaluates the physiological data of patients. The evaluation formula is:

[0047] Z = β 0 + β 1 X + β 2 Y + ∈

[0048] Where Z is the evaluation value of the patient's physiological data, β 0 is the intercept, β 1 and β 2 are regression coefficients, ∈ is the error term, X is the independent variable; Y is the dependent variable, where the regression coefficient β 1 is calculated by the formula:

[0049]

[0050] where n is the number of samples, X i and Y i are the values of the independent and dependent variables of the i-th sample, and are the average values of the independent and dependent variables. The obtained historical data is used as a data sample for verification;

[0051] The intercept β 0 is calculated by the formula:

[0052]

[0053] The value of the intercept is obtained by formula calculation.

[0054] The analysis module analyzes the pulse condition based on the obtained pulse data. The analysis includes the frequency and intensity of the pulse. The pulse frequency is the number of pulse beats detected per unit time, which is the pulse frequency; the pulse intensity calculation formula is: record a series of pulse amplitude values, A 1 , A 2 ... A n , and the amplitude calculation formula is:

[0055]

[0056] where is the calculated average pulse amplitude value, A i is the i-th pulse amplitude value;

[0057] Combining the pulse amplitude value and the pulse frequency, based on the analysis results of the pulse frequency and amplitude value, a comprehensive judgment is made and calculated based on the weighted average formula:

[0058]

[0059] where B is the comprehensive evaluation value of the patient's pulse, C is the pulse frequency, W i is the weight.

[0060] Based on the comprehensive analysis of the patient's physiological parameters and pulse parameters, it is determined whether the patient is in a safe anesthesia state during the anesthesia process. The evaluation formula is: F = Z + B, where F is the value of the comprehensive evaluation. Based on the expert analysis method, the safe threshold range value is given. The safe threshold range value is compared with the comprehensive evaluation value F. When it is greater than the safe threshold range, it is determined that there is an anesthesia risk, and the physician makes timely adjustments. When it is less than the safe threshold range, it is determined that there is no anesthesia risk, and the subsequent operations are continued.

[0061] Through the comprehensive analysis by combining physiological parameters and pulse parameters, this application can comprehensively understand the patient's physical condition during the anesthesia process from multiple perspectives. Physiological parameters such as body temperature and electromyogram reflect the functional states of various systems of the patient's body, while pulse parameters provide key information about the cardiovascular system. The combination of the two can more accurately evaluate the patient's overall state. A single physiological parameter or pulse parameter may have limitations and cannot fully reflect the patient's anesthesia safety state, while the comprehensive evaluation can overcome this limitation and improve the accuracy and reliability of the judgment.

[0062] The display module is used to display the results of data acquisition in real time, providing an intuitive observation window for the physician. The display module uses a high-resolution display screen to clearly present the data of various physiological parameters and pulse conditions. When the data acquisition module transmits the real-time acquired patient physiological parameters and pulse conditions, the display module responds quickly, processes and displays the data, and displays it on the screen in digital form.

[0063] In this application, the physician can intuitively see the data of various physiological parameters and pulse conditions through the high-resolution display screen. Without complex data interpretation and analysis, the physician can quickly master the patient's current state in a short time. This helps the physician make a preliminary judgment quickly in case of emergency and provides an important basis for subsequent treatment decisions. Since the display module can display the results of data acquisition in real time, the physician can continuously observe the dynamic changes of the patient's physiological parameters and pulse conditions, which is particularly important for patients during the anesthesia process because the patient's physical condition may change at any time under anesthesia. Detecting these changes in a timely manner allows the physician to take corresponding measures to ensure the patient's safety.

[0064] The display module provides a function to query historical data, enabling the physician to review the patient's physiological parameters and pulse conditions at different time points. The display module is personalized according to the physician's needs, including adjusting the display color, font size, and data refresh frequency.

[0065] Doctors in this application can query historical data to review the patient's physiological parameters and pulse conditions at different time points, so as to comprehensively understand the development trend of the patient's condition. This helps doctors better evaluate the patient's overall health status and formulate more accurate treatment plans. The query function of historical data enables doctors to conduct comparative analysis on data at different time points. Doctors can compare the changes in physiological parameters of the patient before anesthesia, during anesthesia, and after anesthesia, so as to judge the impact of anesthesia on the patient's body. This comparative analysis can help doctors detect problems in a timely manner and take corresponding measures for adjustment.

[0066] When the analysis module determines through data analysis that there are anesthesia risks for the patient, the warning module responds and emits a strong warning signal. The warning module uses various methods for warning, emitting a loud and rapid sound and light alarm. Through the flashing light and sharp sound, doctors can be aware of the abnormal situation.

[0067] This application uses a loud and rapid sound and light alarm, combining the flashing light with the sharp sound, which can greatly improve the doctor's alertness. The dual stimulation of vision and hearing can more effectively attract the doctor's attention and ensure that the warning can be detected in a timely manner even in a noisy environment.

[0068] After the warning is issued, the doctor makes adjustments to re-evaluate and adjust the patient's anesthesia status, and analyzes the reasons for the anesthesia risks of the patient, including improper anesthesia drug dosage, abnormal reaction of the patient's body to anesthesia, or other unexpected situations.

[0069] This application analyzes the reasons for the anesthesia risks of the patient to help doctors take preventive measures to avoid similar problems from occurring again in future surgeries. If it is found that the risk is caused by improper anesthesia drug dosage, the doctor can calculate and adjust the drug dosage more carefully in future surgeries. If the patient's body has an abnormal reaction to anesthesia, the doctor can make preparations in advance and take corresponding countermeasures.

[0070] The above shows and describes the basic principles, main features and advantages of the present invention. Those skilled in the art of this industry should understand that the present invention is not limited by the above embodiments. What is described in the above embodiments and the specification is only the principle of the present invention. Without departing from the spirit and scope of the present invention, the present invention will have various changes and improvements, and these changes and improvements all fall within the scope of the present invention claimed.

Claims

1. Real-time data acquisition and analysis system for anesthesia process, characterized by: include: Data acquisition module, transmission module, analysis module, display module and warning module; The data acquisition module includes various sensors and pulse monitoring units, which are used to collect the patient's physiological parameters and pulse conditions during anesthesia; The transmission module transmits the physiological parameters and pulse conditions collected in real time to the analysis module; The analysis module analyzes the patient's physiological parameters and pulse conditions based on a linear regression model, and comprehensively analyzes the patient's physiological parameters and pulse parameters to determine whether the patient is in a safe anesthesia state during anesthesia; The display module is used to display the results of data collection in real time for the physician to observe intuitively; When the warning module analysis module determines that the patient has anesthesia risks, it issues a warning to alert the physician and make anesthesia adjustments.

2. The real-time data acquisition and analysis system for anesthesia process according to claim 1, characterized in that: The data acquisition module includes a body temperature sensor and an electromyography sensor. The body temperature sensor is used to monitor changes in the patient's body temperature. It uses an infrared body temperature sensor to obtain body temperature conditions by detecting the intensity of infrared radiation emitted by the human body. The electromyography sensor collects electrical signals generated by muscle contraction and relaxation by bringing the electrode patch into contact with the patient's muscles, and obtains a waveform reflecting electromyography activity after amplification and filtering. The pulse monitoring unit captures changes in the patient's pulse based on the sensor, detects the frequency, intensity and regularity of the pulse in real time, and provides information on the status of the patient's cardiovascular system through continuous monitoring.

3. The real-time data acquisition and analysis system for anesthesia process according to claim 1, characterized in that: The transmission module transmits the real-time collected physiological parameters and pulse conditions to the analysis module using high-quality data lines and interfaces. When the various sensors in the data acquisition module collect the patient's physiological parameters and the pulse monitoring unit monitors the patient's pulse condition, the transmission module responds quickly, packages the data and sends it out. During the transmission process, the data is verified and error-corrected in real time. If any abnormality or loss is found in the data, it will be retransmitted immediately.

4. The real-time data acquisition and analysis system for anesthesia process according to claim 1, characterized in that: The analysis module evaluates the patient's physiological data based on the acquired physiological data. The evaluation formula is: Z=β0+β1X+β2Y+∈ Where Z is the evaluation value of the patient's physiological data, β0 is the intercept, β1 and β2 are regression coefficients, ∈ is the error term, X is the independent variable; Y is the dependent variable, and the calculation formula of the regression coefficient β1 is: Where n is the number of samples, X i With Y i are the values ​​of the independent and dependent variables of the ith sample, and is the average value of the independent variable and the dependent variable, and the historical data obtained are used as data samples for verification; The calculation formula for intercept β0 is: The value of the intercept is calculated using the formula.

5. The real-time data acquisition and analysis system for anesthesia process according to claim 1, characterized in that: The analysis module analyzes the pulse condition based on the acquired pulse data, including the pulse frequency and pulse strength. The pulse frequency is the number of pulse beats detected per unit time, which is the pulse frequency. The pulse strength calculation formula is: record a series of pulse amplitude values, A1, A2...A n , the amplitude calculation formula is: in is the calculated average pulse amplitude, A i is the i-th pulse amplitude value; Combining the pulse amplitude and pulse frequency, a comprehensive judgment is made based on the analysis results of the pulse frequency and amplitude, and the calculation is based on the weighted average formula: Where B is the pulse value of the patient for comprehensive evaluation, C is the frequency of the pulse, and W is the pulse frequency. i is the weight.

6. The real-time data acquisition and analysis system for anesthesia process according to claim 1, characterized in that: A comprehensive analysis is performed based on the patient's physiological parameters and pulse parameters to determine whether the patient is in a safe anesthesia state during anesthesia. The evaluation formula is: F=Z+B, where F is the value of the comprehensive evaluation. A safe threshold range value is given based on the expert analysis method. The safe threshold range value is compared with the comprehensive evaluation value F. When it is greater than the safe threshold range, it is judged that there is an anesthesia risk, and the physician makes timely adjustments. When it is less than the safe threshold range, it is judged that there is no anesthesia risk, and subsequent operations continue.

7. The real-time data acquisition and analysis system for anesthesia process according to claim 1, characterized in that: The display module is used to display the results of data collection in real time, providing doctors with an intuitive observation window. The display module uses a high-resolution display screen to clearly present data on various physiological parameters and pulse conditions. When the data acquisition module transmits the patient's physiological parameters and pulse conditions collected in real time, the display module responds quickly, processes and displays the data, and displays it on the screen in digital form.

8. The real-time data acquisition and analysis system for anesthesia process according to claim 7, characterized in that: The display module provides a historical data query function, allowing doctors to review the patient's physiological parameters and pulse conditions at different time points. The display module is personalized according to the doctor's needs, including adjusting the display color, font size and data refresh frequency.

9. The real-time data acquisition and analysis system for anesthesia process according to claim 1, characterized in that: When the analysis module determines through data analysis that the patient has anesthesia risks, the warning module responds and sends out a strong warning signal. The warning module uses multiple methods to warn, issuing loud and rapid sound and light alarms, allowing doctors to detect abnormal situations through flashing lights and sharp sounds.

10. The real-time data acquisition and analysis system for anesthesia process according to claim 9, characterized in that: After the warning is issued, the physician makes adjustments, re-evaluates and adjusts the patient's anesthesia status, and analyzes the causes of the patient's anesthesia risks, including improper dosage of anesthetic drugs, abnormal response of the patient's body to anesthesia, or other emergencies.

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