Breathing driving state evaluation method based on lung electrical impedance tomography and application

Abstract

The invention belongs to the field of respiratory driving evaluation, and provides a respiratory driving state evaluation method and system based on lung electrical impedance tomography aiming at the problem that traditional inspiration effort measurement operation steps are complex. The method comprises the steps that the inspiration flow rate of a patient to be monitored is obtained based on EIT equipment, and a respiratory flow rate time curve is obtained; determining a nonlinear model of the inspiration flow velocity changing along with the time waveform based on the inspiration flow velocity time curve; determining the value of a concavity index of the respiratory flow rate time curve according to the nonlinear model; and evaluating the inspiration effort degree of the to-be-monitored patient according to the value of the concavity index. According to the method, on the basis of the EIT technology, insertion of any catheter is not needed, the concavity of the flow velocity-time curve is analyzed, evaluation of the respiratory driving force is achieved, and a basis is provided for precise treatment.

Description

Technical Field

[0001] The present invention relates to the technical field of lung recruitment assessment, and in particular to a respiratory drive state assessment method based on pulmonary electrical impedance tomography and its application. Background Art

[0002] Mechanical ventilation is a commonly used life support method in intensive care units (ICUs), particularly for patients with acute respiratory distress syndrome (ARDS) and other severe respiratory diseases. These patients often require varying degrees of respiratory support, and pressure support ventilation (PSV) is one commonly used mode of respiratory support. PSV provides additional pressure to assist the patient's inspiratory effort, aiming to reduce the workload of the respiratory muscles, improve oxygenation, and promote patient comfort.

[0003] When pressure support ventilation (PSV) is performed on patients, the setting of the PSV level is particularly important. This is because when setting the PSV level, it is necessary to provide sufficient support to reduce the load on the respiratory muscles, while avoiding excessive support that may cause lung damage. How to strike a balance between the two to achieve the appropriate setting of the PSV level remains a challenge in current clinical work. Inappropriate PSV levels may cause asynchrony between the patient and the ventilator, increase the load on the patient's respiratory muscles, cause respiratory muscle fatigue, lung damage, and even affect the patient's recovery process. Therefore, accurately assessing the patient's inspiratory effort is crucial for adjusting the PSV level, optimizing the synchronization between the patient and the ventilator, and preventing respiratory muscle damage.

[0004] Currently, common methods for measuring inspiratory effort include pressure measurement, flow monitoring, electrophysiological methods, and imaging techniques. Among these pressure measurements, maximum inspiratory pressure (MIP) and esophageal pressure (Pes) are commonly used indicators. Maximum inspiratory pressure is measured by having the patient inhale forcefully against an obstruction, while esophageal pressure requires placement of a catheter to directly measure intrathoracic pressure. However, these procedures are complex and require catheter placement, which can cause patient discomfort or complications. Flow monitoring typically involves analyzing inspiratory flow rate and tidal volume using a flow sensor. However, the equipment is bulky and expensive, and requires the patient to remain still, making dynamic monitoring difficult. Electrophysiological methods record diaphragmatic electrical signals using surface or esophageal electrodes, but signal strength is easily affected by electrode position and skin impedance, resulting in inaccurate results. Imaging techniques generally involve ultrasound observation of diaphragmatic movement and thickness changes, relying on operator experience and resulting in highly subjective results. Magnetic resonance imaging (MRI) is time-consuming and extremely expensive, making it unsuitable for clinical use.

[0005] Pulmonary electrical impedance tomography (EIT) is a non-invasive monitoring technique that works by applying a low current around the chest and measuring changes in the impedance of the lungs. This provides real-time images of pulmonary ventilation and blood flow distribution, enabling real-time monitoring of pulmonary ventilation distribution and lung condition. Currently, this technique is widely used to assess various lung conditions, including pulmonary ventilation distribution, lung recruitment maneuvers, and pulmonary edema. This present invention, based on EIT technology, assesses respiratory drive by monitoring regional pulmonary impedance changes in real time. Summary of the Invention

[0006] In response to the shortcomings of the above-mentioned prior art, the present invention proposes a respiratory drive status assessment method and system based on pulmonary electrical impedance imaging, which assesses respiratory drive by real-time monitoring of the concavity of the flow velocity time curve and is suitable for mechanically ventilated patients or non-mechanically ventilated patients.

[0007] In a first aspect, the present invention discloses a method for assessing respiratory drive state based on pulmonary electrical impedance imaging, comprising:

[0008] Obtain the inspiratory flow rate of the patient to be monitored based on the EIT device and obtain a respiratory flow rate time curve;

[0009] Based on the respiratory flow rate time curve, a nonlinear model of the change of the inspiratory flow rate waveform with time is determined;

[0010] Determining a value of a concavity index of a respiratory flow rate time curve according to a nonlinear model;

[0011] The inspiratory effort of the patient to be monitored is assessed based on the value of the concavity index.

[0012] Furthermore, the nonlinear model is:

[0013]

[0014] Where V is the inspiratory flow rate, a is the intercept, b is the flow rate decay rate, and c is the concavity index.

[0015] Furthermore, the value of the concavity index is positively correlated with the patient's respiratory effort.

[0016] Furthermore, the step of evaluating the inspiratory effort of the patient to be monitored according to the value of the concavity index includes:

[0017] If the value of the concavity index is less than or equal to the first threshold, it indicates that the patient's inspiratory effort is low and a spontaneous breathing trial can be performed;

[0018] If the value of the concavity index is greater than the first threshold, it indicates that the patient's inspiratory effort is high. Then, it is determined whether the value of the concavity index is greater than the second threshold. If so, it indicates that the patient's inspiratory effort is too high and the spontaneous breathing trial is delayed. If not, the current pressure support ventilation level is readjusted and the inspiratory effort is reassessed.

[0019] Furthermore, the first threshold is 2.1, and the second threshold is 2.4.

[0020] In a second aspect, the present invention discloses a respiratory drive state assessment system based on pulmonary electrical impedance imaging, which is implemented based on the respiratory drive state assessment method based on pulmonary electrical impedance imaging. The system includes:

[0021] A data acquisition module is used to obtain the inspiratory flow rate of the patient to be monitored based on the EIT device and obtain a respiratory flow rate time curve;

[0022] A data analysis module is used to determine a nonlinear model of the inspiratory flow rate waveform change over time based on the respiratory flow rate time curve, and determine the value of the concavity index of the respiratory flow rate time curve through the nonlinear model;

[0023] The respiratory effort evaluation module is used to evaluate the inspiratory effort of the monitored patient according to the value of the concavity index.

[0024] Furthermore, the system further comprises:

[0025] A report generation module, used for generating an inspiratory effort assessment report for the patient to be monitored;

[0026] Data management and storage module, used to save all collected raw data and analysis results in the database;

[0027] The data query module is used to query the evaluation results in the database based on the patient ID or test date.

[0028] In a third aspect, an embodiment of the present application provides an electronic device comprising a memory, a processor, and a computer program stored on the memory, wherein the processor executes the computer program to implement the steps in the respiratory drive state assessment based on pulmonary electrical impedance imaging as described in any one of the above items.

[0029] In a fourth aspect, an embodiment of the present application provides a readable storage medium, on which a program or instruction is stored. When the program or instruction is executed by a processor, the steps in the respiratory drive state assessment based on pulmonary electrical impedance imaging as described above are implemented.

[0030] Therefore, the present invention adopts the above-mentioned respiratory drive state assessment method and system based on pulmonary electrical impedance imaging, which has the following beneficial effects:

[0031] First, compared with traditional methods, this invention, based on EIT technology, does not require any catheter insertion, reducing the risk of infection and discomfort for patients. Furthermore, it can continuously and in real time monitor data, facilitating timely adjustments to respiratory support strategies and optimizing patients' respiratory management.

[0032] Second, the parameters used to assess inspiratory effort in the present invention are calculated based on standard respiratory waveforms and are easily implemented on various ventilators without requiring additional equipment or complex operations. Furthermore, the present invention avoids the complex step of measuring transpulmonary pressure required in traditional methods and can also assess regional respiratory drive, providing a basis for precise treatment.

[0033] Third, by accurately assessing inspiratory effort, the present invention helps adjust PSV levels, reduces asynchrony between the patient and the ventilator, and improves ventilation efficiency. It also helps doctors promptly detect overventilation or hypoventilation, allowing them to take measures to prevent respiratory muscle damage.

[0034] Fourth, the present invention significantly improves the accuracy and reliability of the measurement by first adaptively filtering the original EIT signal, then extracting the respiration-related signal components through wavelet transform, and finally applying a curve fitting algorithm to calculate the evaluation parameters of the inspiratory effort;

[0035] Fifth, an early warning mechanism based on assessment parameters. By setting thresholds and analyzing trends, the system can automatically identify abnormalities in work of breathing and promptly alert doctors to intervene. This intelligent monitoring method greatly improves the efficiency and safety of patient management.

[0036] In summary, the present invention is suitable for various clinical conditions requiring mechanical ventilation, including ARDS, acute exacerbation of COPD, postoperative respiratory support, etc. By providing an objective quantitative indicator, it helps to standardize the adjustment process of respiratory support and reduce the influence of subjective judgment, thereby providing a new and effective tool for the assessment of inspiratory effort in mechanically ventilated patients, which is expected to improve patients' respiratory management and enhance clinical treatment effects.

[0037] The technical solution of the present invention is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] Figure 1 This is a flow chart of the respiratory drive state assessment method based on pulmonary electrical impedance imaging proposed in the present invention.

[0039] Figure 2 is the global impedance image;

[0040] Figure 3 is the tidal image waveform;

[0041] Figure 4 is the calculation result of the evaluation parameters;

[0042] Figure 5 It is the comparison process between FlowIndex and threshold;

[0043] Figure 6 This is the Flow Index change curve of patient Case 1;

[0044] Figure 7 This is the Flow Index change curve of case 2. DETAILED DESCRIPTION

[0045] The exemplary embodiments of the present application will be described in more detail below in conjunction with the accompanying drawings in the embodiments of the present application. Although the accompanying drawings show exemplary embodiments of the present application, it should be understood that the present application can be implemented in various forms and should not be limited by the embodiments set forth herein. On the contrary, these embodiments are provided to enable a more thorough understanding of the present application and to fully convey the scope of the present application to those skilled in the art.

[0046] Example 1

[0047] Reference Figure 1 , Figure 1 This embodiment provides a method for assessing respiratory drive status based on pulmonary electrical impedance imaging, which may include:

[0048] Step 1: Obtain the inspiratory flow rate of the patient to be monitored and obtain the respiratory flow rate time curve;

[0049] In an embodiment of the present application, an EIT device is first placed around the patient's chest via a sensor electrode array to monitor changes in the patient's chest electrical impedance, thereby reflecting the patient's lung ventilation and blood flow distribution, thereby monitoring the patient's respiratory waveform data in real time through the EIT device;

[0050] Among them, respiratory waveform data generally includes pressure waveform, flow waveform, volume waveform and time parameters. The patient's inspiratory flow rate (flow) can be obtained from the respiratory waveform data, thereby establishing a respiratory flow rate time curve;

[0051] Record the patient's basic respiratory waveform data when they are in a stable state for subsequent comparative analysis.

[0052] The patient referred to in this application is a patient who is ready for a spontaneous breathing trial. A spontaneous breathing trial (SBT) involves using a T-tube or low-support spontaneous breathing mode on an invasively ventilated patient. Through short-term dynamic observation, the patient's ability to tolerate spontaneous breathing is evaluated. This is a relatively reliable method for determining successful weaning.

[0053] Step 2: Based on the respiratory flow rate time curve, determine the nonlinear model of the inspiratory flow rate waveform change over time;

[0054] Based on the obtained patient's inspiratory flow rate and time, a flow rate time curve can be obtained to describe the change of the patient's inspiratory flow rate over time. The concavity of the flow rate time curve can be obtained by a nonlinear model of the flow rate time curve. The nonlinear model is:

[0055]

[0056] Where V is the inspiratory flow rate, a is the initial resistance value of the inspiratory flow rate, b is the resistance flow rate decay rate, c is the concavity index, and time is the current time;

[0057] The decay pattern of the inspiratory flow curve is described by the nonlinear model described above. This model captures the relationship between inspiratory flow and time, and the concavity of the flow curve is represented by the concavity index c (i.e., FlowIndex, abbreviated as FI). The concavity index can be used to assess the patient's respiratory effort.

[0058] By recording the concavity index c value for each measurement for long-term tracking and analysis, the collected data were statistically analyzed to assess the correlation between the concavity index c and the patient's respiratory effort. Smaller concavity index values ​​indicate lower respiratory effort, while larger values ​​indicate higher respiratory effort. In other words, the concavity index value is positively correlated with the patient's respiratory effort.

[0059] Step 3: Determine the value of the concavity index using the nonlinear model;

[0060] In formula (1), the inspiratory flow rate can be obtained by monitoring the inspiratory resistance value through EIT. Both a and b are known values. Therefore, the value of the concavity index (Flow Index) is calculated by the above formula (1). In addition, according to EIT, regional (such as dorsal, thoracic, etc.) impedance changes can be obtained to obtain regional inspiratory flow rate, thereby using the concavity index (Flow Index) to achieve regional respiratory driving force assessment, thereby realizing the transition from simple ventilation distribution monitoring to mechanical mechanism assessment.

[0061] Step 4: Based on the value of the concavity index, assess the inspiratory effort of the patient to be monitored.

[0062] In an embodiment of the present application, the calculated value of the concavity index is compared with a first threshold:

[0063] If the value of the concavity index is less than or equal to the first threshold, it indicates that the patient's inspiratory effort is low and a spontaneous breathing trial can be performed;

[0064] If the value of the concavity index is greater than the first threshold, it indicates that the patient's inspiratory effort is high. Then, it is determined whether the value of the concavity index is greater than the second threshold. If so, it indicates that the patient's inspiratory effort is too high and the spontaneous breathing trial should be delayed. If not, the current pressure support ventilation level is readjusted and the process returns to the first step to reassess the inspiratory effort.

[0065] The first threshold and the second threshold can be determined based on the respiratory waveform and time waveform data of the patient in a stable state. The first threshold is 2.1, and the second threshold is 2.4.

[0066] Combine Figure 5 When the concavity index (FI) value is less than or equal to 2.1, it indicates that the patient can undergo the SBT test, and the predicted success rate is high. During the SBT, the Flow Index value is continuously monitored every 15 minutes. If the increase in the Flow Index value is less than 15%, the SBT is continued. Otherwise, the SBT is terminated and respiratory muscle rehabilitation is performed;

[0067] When the concavity index is greater than 2.1 and less than or equal to 2.4, the current pressure support ventilation (PSV) level is readjusted and reassessed;

[0068] When the Flow Index is greater than 2.4, the SBT should be postponed and clinical evaluation should be performed to identify potential abnormalities in respiratory drive.

[0069] For the concavity index, a higher value indicates a greater inspiratory effort, while a lower value may indicate insufficient inspiratory effort or hyperventilation. The value of the concavity index can provide an objective quantitative indicator for clinical assessment.

[0070] Based on the patient's inspiratory effort assessment, the doctor can adjust the pressure support ventilation (PSV) level to optimize the patient's respiratory support. Specifically, the doctor compares the patient's inspiratory effort with the level of support provided by the ventilator to assess the synchrony between the patient and the ventilator. If the patient's inspiratory effort is too high, the PSV level is increased; conversely, if it is too high, the PSV level is decreased.

[0071] The EIT device can continuously monitor the value of the concavity index and continuously evaluate the treatment effect after adjusting the respiratory support level to ensure that the patient's respiratory muscles are properly supported while avoiding hyperventilation.

[0072] Through these steps, a real-time, quantitative tool is provided for clinicians to assess and optimize respiratory support for mechanically ventilated patients. Its advantages lie in its non-invasiveness, real-time nature, and ability to provide objective data on the patient's inspiratory effort, thereby helping to improve the patient's respiratory management and clinical prognosis.

[0073] Based on the evaluation method provided in this embodiment, its effectiveness was verified through the following two cases.

[0074] (1) Cases of successful weaning from ventilators

[0075] Case 1: A 65-year-old male was admitted to the hospital for ARDS secondary to pneumonia and was receiving mechanical ventilation for 7 days. He had no prior pulmonary comorbidities. His Flow Index values ​​were monitored. The values ​​of the ventral and dorsal concavity indexes for this case are shown in the last column of Table 1. Δ% represents the percentage increase in Flow Index. The Flow Index change curve for this case is shown in Figure 6 shown.

[0076] Table 1

[0077]

[0078] It can be seen that the Flow Index showed a steady upward trend, and the patient was finally successfully removed from the ventilator at the 126th minute.

[0079] (2) Cases of failure to wean from ventilator

[0080] Case 2: A 58-year-old female was admitted to the hospital with septic shock and received mechanical ventilation for 10 days. She also had COPD (GOLD stage 2). Her Flow Index values ​​were monitored, and the results are shown in Table 2. The Flow Index curve is shown in Figure 7 shown.

[0081] Table 2

[0082]

[0083] As can be seen from Table 2, the Flow Index value increased rapidly and was greater than 2.4. Finally, the SBT was terminated at the 68th minute due to dyspnea and the patient failed to be weaned from the ventilator.

[0084] Example 2

[0085] This application utilizes the above-mentioned respiratory drive state assessment method based on pulmonary electrical impedance imaging to design a respiratory drive assessment system based on pulmonary electrical impedance imaging, which may include:

[0086] A data acquisition module, used to collect the inspiratory flow rate and time waveform of the patient to be monitored to obtain a flow rate time curve;

[0087] In this embodiment, the inspiratory flow rate and time waveform of the patient to be monitored are collected by the EIT device, and the collected data can be displayed through the interface. The real-time EIT image collected is displayed on the left, the flow rate time curve is displayed in the middle, and the values ​​of various parameters are displayed on the right, such as Figure 2-Figure 3 shown.

[0088] The system uses a 50Hz sampling frequency to collect data and update the display content in real time. If a signal anomaly is encountered, the system will automatically alarm and display a prompt message in the status bar.

[0089] A data analysis module is used to construct a nonlinear model of the flow velocity time curve and calculate the value of the concavity index through the nonlinear model;

[0090] In this embodiment, the analysis results of the data analysis module are displayed in real time in numerical and graphical form, including: the value of the concavity index c, the respiratory effort level, the regional respiratory drive value, and the trend graph of the concavity index c.

[0091] The respiratory effort assessment module is used to assess the inspiratory effort of the monitored patient according to the value of the concavity index.

[0092] In this module, the evaluation of the inspiratory effort of the patient to be monitored according to the value of the concavity index is the same as the specific steps of step 4 in embodiment 1, and will not be repeated here.

[0093] A report generation module, used for generating an inspiratory effort assessment report for the patient to be monitored;

[0094] In this embodiment, the information included in the inspiratory effort assessment report may be patient information, test data, analysis results, clinical recommendations, and the like.

[0095] The data management and storage module is used to save all collected raw data and analysis results in the database.

[0096] The data query module is used to query the evaluation results in the database based on the patient ID or test date.

[0097] In order to facilitate subsequent statistical analysis or case sharing, this system can support exporting data stored in the database in multiple formats, such as Excel and PDF, and can perform regular data backup to ensure data security.

[0098] This system requires equipment calibration before first use. Ensure the electrodes are correctly positioned and in good contact during use. Regularly check system settings and parameter configurations, and back up important data.

[0099] Clinical application cases

[0100] Patient Wang was admitted to the hospital's intensive care unit (ICU) for acute respiratory failure. After evaluation, the doctor decided to use mechanical ventilation and implement pressure support ventilation (PSV) for the patient. During this period, the system proposed in this invention performed the following specific operations on the patient:

[0101] 1. Enter your account and password on the system login page for identity authentication. After passing the authentication, you will enter the main interface, which adopts a partitioned layout design, including the upper menu bar, left toolbar, central display area and bottom status bar. The menu bar contains the main functional modules such as file, acquisition, analysis, and settings, and the toolbar provides shortcut buttons for commonly used functions;

[0102] 2. Before starting the test, create or select the patient record in the system. If it is a new patient, click the "Create Patient" button and fill in the patient's basic information in the pop-up form, including name, ID, age, gender, diagnosis and other necessary information. At the same time, you can select the test mode (such as real-time monitoring mode or offline analysis mode). After filling in all the information, click Confirm to save;

[0103] 3. Ensure that the EIT device is connected to the ventilator. After connecting the EIT device, enter the device calibration interface and follow the prompts to adjust the electrode belt position and check the signal quality. The system will display the electrode connection status and signal quality indicators in real time on the display page. Ensure that all electrodes are in good contact (contact quality > 90%) and the signal-to-noise ratio meets the requirements (> 10dB).

[0104] 4. After calibration is complete, click the "Start Acquisition" button to start the data acquisition model, collect the patient's inspiratory flow rate and time waveform, and display the real-time EIT image, flow rate time curve, and various parameter values ​​in the display area;

[0105] 5. Based on the collected values, the system calculates through the data analysis module to obtain the value of the concavity index;

[0106] 6. Based on the obtained concavity index value, the system uses the respiratory effort assessment module to evaluate the patient's inspiratory effort and displays the analysis results in real time on the display interface in numerical and graphical form;

[0107] 7. During the above process, the system's data management and storage module will automatically save all the data obtained;

[0108] 8. Based on the results of the inspiratory effort assessment, compare the patient's inspiratory effort with the level of support provided by the ventilator to see if they are synchronized. If the patient's inspiratory effort is too high, increase the level of pressure support ventilation (PSV); otherwise, decrease the level of pressure support ventilation (PSV);

[0109] 9. Continuously monitor changes in the concavity index value to assess the therapeutic effect after adjusting respiratory support, ensure that the patient's respiratory muscles are appropriately supported, and avoid hyperventilation.

[0110] An embodiment of the present application also provides a computer-readable storage medium having a computer program / instruction stored thereon. When the computer program / instruction is executed by a processor, the steps in the respiratory drive state assessment method based on pulmonary electrical impedance imaging as disclosed in the embodiment of the present application are implemented.

[0111] An embodiment of the present application further provides a computer program product, which, when executed on an electronic device, enables a processor to implement the steps of the respiratory drive state assessment method based on pulmonary electrical impedance imaging as disclosed in the embodiment of the present application.

[0112] The various embodiments in this specification are described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the various embodiments can be referenced to each other.

[0113] The embodiments of the present application are described with reference to the flowcharts and / or block diagrams of the methods, apparatuses, electronic devices, and computer program products according to the embodiments of the present application. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of the processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing terminal device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing terminal device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0114] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing terminal device to operate in a specific manner, so that the instructions stored in the computer readable memory produce a manufactured product including an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0115] These computer program instructions can also be loaded onto a computer or other programmable data processing terminal device so that a series of operating steps are executed on the computer or other programmable terminal device to produce a computer-implemented process, thereby providing instructions for executing on the computer or other programmable terminal device to implement the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0116] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit the same. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that they can still modify or replace the technical solutions of the present invention with equivalents, and these modifications or equivalent replacements cannot cause the modified technical solutions to deviate from the spirit and scope of the technical solutions of the present invention.

Claims

1. A respiratory drive state assessment method based on pulmonary electrical impedance tomography, characterized in that: The method includes: Obtain the inspiratory flow rate of the patient to be monitored based on the EIT device and obtain a respiratory flow rate time curve; Based on the respiratory flow rate time curve, a nonlinear model of the change of the inspiratory flow rate waveform with time is determined; Determining a value of a concavity index of a respiratory flow rate time curve according to a nonlinear model; The inspiratory effort of the patient to be monitored is assessed based on the value of the concavity index.

2. The respiratory drive state assessment method based on pulmonary electrical impedance tomography according to claim 1, wherein: The nonlinear model is: Where V is the inspiratory flow rate, a is the intercept, b is the flow rate decay rate, and c is the concavity index.

3. The respiratory drive state assessment method based on pulmonary electrical impedance imaging according to claim 2, characterized in that: The value of the concavity index is positively correlated with the patient's respiratory effort.

4. The respiratory drive state assessment method based on pulmonary electrical impedance imaging according to claim 1, wherein: The step of evaluating the inspiratory effort of the patient to be monitored according to the value of the concavity index includes: If the value of the concavity index is less than or equal to the first threshold, it indicates that the patient's inspiratory effort is low and a spontaneous breathing trial can be performed; If the value of the concavity index is greater than the first threshold, it indicates that the patient's inspiratory effort is high. Then, it is determined whether the value of the concavity index is greater than the second threshold. If so, it indicates that the patient's inspiratory effort is too high and the spontaneous breathing trial is delayed. If not, the current pressure support ventilation level is readjusted and the inspiratory effort is reassessed.

5. The respiratory drive state assessment method based on pulmonary electrical impedance imaging according to claim 4, characterized in that: The first threshold is 2.1, and the second threshold is 2.

4.

6. A respiratory drive state assessment system based on pulmonary electrical impedance imaging, characterized in that: The system includes: A data acquisition module is used to obtain the inspiratory flow rate of the patient to be monitored based on the EIT device and obtain a respiratory flow rate time curve; A data analysis module is used to determine a nonlinear model of the inspiratory flow rate waveform change over time based on the respiratory flow rate time curve, and determine the value of the concavity index of the respiratory flow rate time curve through the nonlinear model; The respiratory effort evaluation module is used to evaluate the inspiratory effort of the monitored patient according to the value of the concavity index.

7. A respiratory drive state assessment system based on pulmonary electrical impedance imaging according to claim 6, characterized in that: Also includes: A report generation module, used for generating an inspiratory effort assessment report for the patient to be monitored; Data management and storage module, used to save all collected raw data and analysis results in the database; The data query module is used to query the evaluation results in the database based on the patient ID or test date.

8. An electronic device comprising a memory, a processor, and a computer program stored in the memory, wherein the processor executes the computer program to implement the steps in the method for assessing respiratory drive state based on pulmonary electrical impedance imaging according to any one of claims 1 to 5.

9. A readable storage medium storing a program or instruction, wherein the program or instruction, when executed by a processor, implements the steps of the respiratory drive state assessment method based on pulmonary electrical impedance imaging according to any one of claims 1 to 5.

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