Method for obtaining spontaneous respiration effort curve under mechanical ventilation based on breathing machine waveform

Abstract

The invention discloses a method for acquiring a spontaneous respiration effort curve under mechanical ventilation based on a breathing machine waveform, which comprises the following steps of: firstly, calculating resistance and compliance in a respiratory system of a patient through airway pressure and flow velocity waveforms when the breathing machine ventilates the patient; and calculating the spontaneous respiration effort of the patient during each respiration according to the resistance compliance and the pressure flow velocity waveform. For different patients, the conditions of pressure and resistance changing along with time and an inspiration effort intensity curve of each time can be calculated through the method when each time of respiration is carried out. The contents can help a doctor to better judge the illness state of a patient, so that clinical treatment is better assisted.

Description

Technical Field

[0001] The present invention relates to the field of monitoring the spontaneous breathing effort of patients under mechanical ventilation, and in particular to a method for obtaining a spontaneous breathing effort curve under mechanical ventilation based on a ventilator waveform and a method for monitoring the spontaneous breathing effort of patients under mechanical ventilation. Background Art

[0002] Mechanical ventilation (MV) refers to the use of a ventilator to provide artificial ventilation, either fully or partially. Mechanical ventilation helps move air in and out of the lungs, with the main goal of helping deliver oxygen and remove carbon dioxide. Mechanical ventilation is used for many reasons, including airway obstruction due to various reasons, the need to ensure adequate oxygenation of the patient, or to remove excess carbon dioxide from the lungs. Proper ventilator management is a particular concern for patients.

[0003] Currently, the estimation of patient-specific respiratory mechanics has shown certain results in optimizing patient-specific mechanical ventilation. However, for patients with spontaneous breathing (SB), additional equipment or invasive clinical procedures are required to determine the patient's true respiratory mechanics. This is because the patient's own respiratory efforts blur the observation of model-based lung mechanics. Therefore, estimating respiratory mechanics to guide MV is currently limited to fully sedated patients, and is often less reliable when the patient is semi-conscious or awake because of the presence of spontaneous breathing. This problem greatly limits the use of model-based methods.

[0004] During supportive mechanical ventilation, the patient's spontaneous breathing efforts can trigger the ventilator, enabling the ventilator to support the patient's inspiratory efforts. Insufficient or excessive ventilator support may cause discomfort, fear, and even lung damage, which may cause stress and prolong ventilation time. Inspiratory force is also an important parameter for follow-up recovery of critically ill patients and a determining factor for successful weaning from the ventilator. Therefore, it is clinically necessary to reliably monitor the inspiratory force of patients in the intensive care unit during supported mechanical ventilation.

[0005] In recent years, there are many methods for estimating the intensity of spontaneous breathing efforts. There are model-based methods. For example, Francesco, Daniel P Redmond, Ganesa and others are based on different spontaneous breathing models, and then use the least squares method based on the ventilator waveform to solve the best fitting value of the breathing parameters. That is, various functions are combined alone or in combination to form a new function to simulate spontaneous breathing. These methods of using functions to simulate inspiratory efforts are limited by the complexity of functions and models and are not easy to obtain better fitting results. At the same time, when facing different patients and different inspiratory efforts of the same patient, model-based methods also need to adjust the setting parameters of the model to fit different patients, which greatly increases the difficulty of using such methods and reduces the efficiency of use.

[0006] Therefore, many methods of using machine learning to study inspiratory efforts have emerged. In the paper, Ang CYS proposed the use of convolutional autoencoders to quantify the magnitude of respiratory effort in spontaneously breathing patients. Assuming that machine learning can reconstruct high-level features from input data, it will provide better prediction accuracy and robustness of the magnitude of spontaneous respiratory effort. The use of machine learning eliminates the need for mathematical modeling of processes with spontaneous respiratory effort and reduces the required computing resources. Therefore, it can be used to evaluate the patient's respiratory status and effort in real time. However, the number of data sets required to train the model is large and inconvenient to use clinically. Summary of the invention

[0007] The purpose of the present invention is to develop a method for obtaining a spontaneous breathing effort curve under mechanical ventilation based on a ventilator waveform in view of the deficiencies in the prior art. The method can first calculate the resistance and compliance in the patient's respiratory system through the airway pressure and flow rate waveforms of the ventilator when the patient is ventilated, and then calculate the size of the patient's spontaneous breathing effort at each breath according to the resistance compliance and pressure flow rate waveforms. For each different patient, the pressure and resistance changes over time and the inhalation effort intensity curve at each breath can be calculated by this method. These contents can help doctors have a better judgment on the patient's condition, thereby better assisting clinical treatment.

[0008] The scheme adopted by the present invention is specifically as follows:

[0009] A method for obtaining a spontaneous breathing effort curve under mechanical ventilation based on a ventilator waveform, comprising:

[0010] Obtain the patient's ventilator waveform data and airway pressure data under mechanical ventilation;

[0011] Based on the acquired ventilator waveform data, calculate the resistance and compliance of the patient's respiratory system at each time point;

[0012] Based on the acquired ventilator waveform data, airway pressure data and the calculated resistance and compliance of the patient's respiratory system at each time point, the inspiratory effort at each time point is calculated using an inspiratory effort formula constructed based on a circuit model of the respiratory system, thereby obtaining the patient's spontaneous respiratory effort curve under mechanical ventilation; wherein, the inspiratory effort formula constructed based on the circuit model of the respiratory system is expressed as follows:

[0013]

[0014] Where P mus For the patient's inspiratory effort, P aw is the patient's airway pressure, V is the flow rate of the airflow, and the integral of the flow rate over time is the tidal volume, R r and Cr are the resistance and compliance of the patient's respiratory system, respectively.

[0015] Furthermore, the ventilator waveform data includes a flow rate-time signal, a pressure-time signal, and a tidal volume-time signal.

[0016] Furthermore, in the calculation of the resistance and compliance of the patient's respiratory system at each time point, the average resistance and average compliance of the patient's respiratory system for each breath are calculated as the resistance and compliance at each time point of the breath.

[0017] Furthermore, in the calculation of the resistance and compliance of the patient's respiratory system at each time point, each breath is divided into the following four stages according to the changes in airway pressure and flow rate: a pressure rise stage, a pressure stable stage, a pressure drop stage and a terminal respiratory stage; the average resistance and average compliance of the patient's respiratory system in each stage of each breath are calculated as the resistance and compliance at each time point in the corresponding stage of the breath.

[0018] Furthermore, the average resistance and average compliance are calculated using the following formula at the end of breathing:

[0019]

[0020] Where d(sumV) represents the change in tidal volume at the end of breathing, d(P) represents the change in pressure at the end of breathing, P = P aw , d(V) represents the change in flow velocity during the end-breathing phase.

[0021] Furthermore, after calculating the resistance and compliance of the patient's respiratory system at each time point, the resistance and compliance of the patient's respiratory system at each time point are smoothed.

[0022] Furthermore, the smoothing process is specifically as follows:

[0023] In the curve composed of the resistance and compliance of the patient's respiratory system at each time point, the value at time s is adjusted to the average value of the data in the time period [sw:s+w] in sequence; where w is the sliding window length.

[0024] A method for monitoring the spontaneous breathing effort of a patient under mechanical ventilation, specifically:

[0025] The method for obtaining a spontaneous breathing effort curve under mechanical ventilation based on a ventilator waveform is used in real time to obtain a patient's spontaneous breathing effort curve under mechanical ventilation, and monitor the patient's spontaneous breathing effort.

[0026] An electronic device comprises a memory, a processor and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, a method for obtaining a spontaneous breathing effort curve under mechanical ventilation based on a ventilator waveform or a method for monitoring the spontaneous breathing effort of a patient under mechanical ventilation is implemented.

[0027] A storage medium containing computer executable instructions, which, when executed by a computer processor, implements a method for calculating a spontaneous breathing effort curve under mechanical ventilation based on a ventilator waveform or a method for monitoring a patient's spontaneous breathing effort under mechanical ventilation.

[0028] A computer program product includes a computer program / instruction, which, when executed by a processor, implements a method for calculating a spontaneous breathing effort curve under mechanical ventilation based on a ventilator waveform or the steps of a method for monitoring the spontaneous breathing effort of a patient under mechanical ventilation.

[0029] Compared with the prior art, the present invention has the following beneficial effects:

[0030] The present invention is a method for calculating the spontaneous breathing effort curve based on the pressure and flow rate waveform of the ventilator. By means of mathematical modeling, a mathematical model of the human respiratory system is established. Based on the mathematical model, the spontaneous breathing effort curve calculation is realized.

[0031] Furthermore, the present invention uses segmented calculation of resistance and compliance to more accurately calculate the changes in resistance and compliance in different time periods in one breath. The segmented calculation fully considers the impact of changes in pressure and flow rate during breathing on resistance and compliance when performing segmentation. A breathing waveform is divided into a pressure rising stage, a pressure stable stage, a pressure falling stage and a terminal respiratory stage. This classification method is mainly based on the change in pressure, and in each time period, the change in flow rate is also monotonic, all of which are monotonically increasing or monotonically decreasing, so the different stages of breathing can be better divided. Distinguishing the first three stages where the inspiratory effort is more obvious from the terminal respiratory stage where there is almost no inspiratory effort, using different calculation methods can also improve the accuracy of resistance and compliance calculation. The segmented calculation of resistance and compliance proposed by the present invention has a certain degree of explanatory power.

[0032] At the same time, when the resistance and compliance change over time, when switching from one time period to another, the resistance and compliance change suddenly, which will cause the calculated inhalation effort to change suddenly and greatly, thereby generating a jitter phenomenon in the waveform. Therefore, in view of this phenomenon, the present invention uses a sliding window to smooth the data of resistance and compliance. By smoothing the resistance and compliance, the jitter phenomenon in the finally calculated inhalation effort can be reduced.

[0033] The resistance and compliance calculated in segments and the subsequent sliding window smoothing process can more accurately calculate the patient's inspiratory effort, providing more support for the research related to the patient's inspiratory effort. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] Figure 1 The present invention is a flowchart of a method for calculating a spontaneous breathing effort curve under mechanical ventilation based on a ventilator waveform according to an embodiment of the present invention.

[0035] Figure 2 This is the circuit model diagram of the ventilator-patient model.

[0036] Figure 3 This is a comparison diagram of the fitted inspiratory effort and esophageal pressure when only the average resistance and compliance are calculated in one embodiment of the present invention.

[0037] Figure 4 This is a comparison diagram of the fitted inspiratory effort and esophageal pressure when the piecewise calculated resistance and compliance are used in one embodiment of the present invention.

[0038] Figure 5 This is a comparison diagram of the fitted inspiratory effort and esophageal pressure when the resistance and compliance after segmented calculation and smoothing are used in one embodiment of the present invention. DETAILED DESCRIPTION

[0039] The preferred embodiments of the present invention will be described in detail below with reference to the accompanying drawings. It should be understood that the preferred embodiments are only for illustrating the present invention, rather than for limiting the protection scope of the present invention.

[0040] The present invention provides a method for obtaining a spontaneous breathing effort curve under mechanical ventilation based on a ventilator waveform, the method comprising the following steps:

[0041] Step 1: Obtain the ventilator waveform data and airway pressure data of the patient under mechanical ventilation;

[0042] Step 2: Based on the acquired ventilator waveform data, calculate the resistance and compliance of the patient's respiratory system at each time point;

[0043] Step 3: Based on the acquired ventilator waveform data, airway pressure data and the calculated resistance and compliance of the patient's respiratory system at each time point, the inspiratory effort at each time point is calculated using the inspiratory effort formula constructed based on the circuit model of the respiratory system, and then the patient's spontaneous breathing effort curve under mechanical ventilation is obtained.

[0044] In the present invention, the inhalation effort formula is constructed based on the circuit model of the respiratory system, wherein the circuit model is used to describe the mechanical part of the model, and the mechanical model is converted into a circuit model. The main contents are: using voltage to describe air pressure, using current to describe airflow, using resistance to describe resistance, and using capacitance to describe elasticity. In this way, the circuit system can be used to represent the respiratory system. The model used in the present invention is a single-chamber model, which regards the entire respiratory system as a whole, and uses a resistor and a capacitor to represent the obstruction of the entire respiratory system to the airflow. Specifically, refer to Figure 2 , build a mathematical model of the patient's respiratory system. Figure 2 It is a model of the interaction between the patient and the ventilator, which is divided into the patient part and the ventilator part. The present invention only considers the patient part. The patient part uses a linear resistor Rr and a linear capacitor Cr to represent the resistance and compliance of the patient's respiratory system; the driving force simulates the realization of spontaneous breathing, that is, the pressure generated by the respiratory muscles (respiratory muscle pressure, P mus ), driving the entire respiratory system mathematical model to generate a respiratory waveform. The specific circuit topology is: respiratory system resistance R r One end is the airway pressure P aw , and the other end is connected to the respiratory system capacitor C r Connected, respiratory system capacitance C r The other end is connected to the driving force voltage source P mus Positive port, driving force voltage source P mus The negative port is grounded. Based on the mass conservation theorem, write the differential equation of the respiratory system. The mass conservation theorem can be described in the circuit as follows: in a branch, the current is equal everywhere. According to the relationship between voltage (U), current (I) and capacitance (C):

[0045]

[0046] The differential equations of the current and voltage at each node can be obtained. By solving the differential equations, the voltage and current at each moment can be obtained.

[0047] According to the established single-chamber model and the law of conservation of mass, a formula for inhalation effort can be derived:

[0048]

[0049] According to the actual meaning of the respiratory system described by the circuit model, we can know that P mus For the patient's inspiratory effort, P aw is the patient's airway pressure, V is the flow rate of the airflow, and the integral of the flow rate over time is the tidal volume, R r and C r are the resistance and compliance of the patient's respiratory system, respectively.

[0050] In a specific embodiment, in step 2, the specific method for calculating the resistance and compliance of the patient's respiratory system at each time point based on the acquired ventilator waveform data is: respectively calculating the average resistance and average compliance of the patient's respiratory system for each breath as the resistance and compliance at each time point of that breath.

[0051] Among them, the patient's resistance and compliance can be obtained by using the patient's airway pressure, flow rate and esophageal pressure data to perform least squares fitting according to the following formula:

[0052]

[0053] In this case, esophageal pressure is used to replace P in the formula mus .

[0054] You can also refer to the compliance calculation method in patent ZL202110049428.5 for calculation.

[0055] The compliance C can also be estimated using the respiratory mechanics motion equation and the least squares algorithm. r and airway resistance R r Estimated value;

[0056] The equation of motion for respiratory mechanics is as follows:

[0057]

[0058] Among them, P(t) represents pressure-time data, F(t) represents flow rate-time data, V(t) represents tidal volume-time data, and PEEP represents positive end-expiratory pressure.

[0059] Furthermore, the average resistance and compliance in one breath and the reliability of the calculation can be calculated by fitting through the least square method. However, in one breath, due to changes in pressure, flow rate and other conditions, the resistance and compliance of the patient's respiratory system will continue to change. Using a single average resistance and compliance in one breath will lead to errors in the process of calculating the inspiratory effort. Therefore, in a more preferred solution, such as Figure 2 As shown, in step 2, based on the acquired ventilator waveform data, the specific method for calculating the resistance and compliance of the patient's respiratory system at each time point is:

[0060] Each breath is calculated based on the changes in airway pressure and flow rate. Figure 1As shown in the figure, the whole breathing process is divided into the following four stages: pressure rising stage, pressure stable stage, pressure falling stage and end-breathing stage; in the pressure rising stage, the airway pressure and flow rate both rise rapidly; in the pressure stable stage, the airway pressure has become stable and has little change, and the flow rate gradually rises to the peak; in the pressure falling stage, the airway pressure drops rapidly to PEEP (positive end-expiratory pressure), and the flow rate also drops rapidly in this stage; in the end-breathing stage, the pressure has stabilized at PEEP, and the flow rate also changes slowly. This classification method is mainly based on the change of pressure, and in each time period, the change of flow rate is monotonic, which is monotonically increasing or monotonically decreasing, so it can better divide the different stages of breathing. On this basis, the average resistance and average compliance of the patient's respiratory system in each stage of each breath are calculated as the resistance and compliance at each time point in the corresponding stage of the breath. Among them, in the first three stages, the use of the least squares method for fitting can obtain a higher degree of fit, so these data can be used. In the terminal respiratory stage, the patient's breathing effort is already relatively weak. At this time, the pressure fitted using the least squares method has low credibility, so the fitted data cannot be used directly. However, if you observe the changes in the waveforms of pressure, flow rate and other waveforms in the second half, you can find that during this period, the changes in pressure, flow rate and other data are very stable. If during this period, the resistance and compliance are fixed values ​​or do not change much, then the more basic resistance and compliance calculation formulas can be used to calculate the resistance and compliance during this period. The calculation formulas are

[0061]

[0062] Where d(sumV) represents the change in tidal volume, and d(P) represents the change in pressure, including the patient's airway pressure and the patient's inspiratory effort. Since the patient's inspiratory effort does not change in the end-of-breathing stage, P = P aw , d(V) represents the change in flow rate. From this, we can get the resistance and compliance in several time periods, and connect them together in chronological order to get the function of resistance and compliance changing with time in one breath. By using a function of resistance and compliance changing with time instead of an average resistance and compliance representing the whole through segmented calculation, the accuracy of the calculation can be improved.

[0063] The average compliance and average resistance of one breath calculated by the above two schemes using the collected real patient waveform data, as well as some results of calculating the resistance and compliance of the patient's respiratory system in four time periods are also recorded in Tables 1 and 2.

[0064] Table 1 Partial results of compliance calculation

[0065]

[0066] Table 2 Partial results of resistance calculation

[0067]

[0068] Furthermore, after calculating the resistance and compliance in segmented time periods, when the resistance and compliance change over time and switch from one time period to another, the data will change suddenly, which will cause problems in the calculation of the data in this switched time period. During this period of time, when calculating the inspiratory effort, due to the sudden change in resistance and compliance, the calculated inspiratory effort will also suddenly change greatly, resulting in a more obvious jitter phenomenon in the waveform. Therefore, in a preferred solution, on the basis of the original data of the resistance and compliance changing over time, it is necessary to add a sliding window to smooth the data of the resistance and compliance, and use a sliding window with a length of 2w to adjust the value at a certain moment s to the average value of the data in the [sw:s+w] time period. The result of this method is that when the resistance and compliance are switched, the data will not suddenly change in a step, but will change gradually in the form of a linear function within a short period of time. The value of w can be adjusted within a certain range. According to the subsequent calculation results, the value of w can be adjusted within a certain range, usually between 7 and 10. Generally, a better result can be obtained when it reaches 8, so that the error between the calculated inspiratory effort and esophageal pressure is low. The final resistance-time curve and compliance-time curve are obtained by sliding window averaging.

[0069] Table 3 shows the change of resistance over time in a certain set of data before and after the resistance switch, reflecting how the sliding window average makes the change of resistance and compliance smoother.

[0070] Table 3 Changes in resistance before and after using the sliding window

[0071]

[0072]

[0073] In this embodiment, the collected ventilator waveform data, esophageal pressure data and airway pressure data of the real patient are used to calculate the patient's resistance and compliance at different times based on the waveform and esophageal pressure data. The inspiratory effort data can be calculated based on the resistance, compliance, airway pressure data and flow rate data and the calculation formula of the inspiratory effort, and then compared with the patient's esophageal pressure P esCompare and verify the accuracy of the calculation results. The quality of the calculation results can be judged by comparing the correlation and total error between the two. Correlation and correlation coefficient are statistical indicators used to reflect the closeness of the correlation between variables. The closer the correlation coefficient is to 1, the stronger the correlation between the two groups of variables. The total error is the sum of the errors between the calculated inspiratory effort and the esophageal pressure at each moment in one breath.

[0074] For the same breath, Figure 3 This is a comparison chart of the fitted inspiratory effort and esophageal pressure when only the average resistance and compliance are calculated. Figure 4 Comparison of fitted inspiratory effort and esophageal pressure when piecewise calculated resistance and compliance are used.

[0075] Figure 5 Comparison of fitted inspiratory effort and esophageal pressure when piecewise-calculated and smoothed resistance and compliance are used.

[0076] The statistical results after calculating multiple sets of data are shown in Table 4:

[0077] Table 4 Correlation coefficient and error between calculated inspiratory effort and esophageal pressure

[0078] Correlation coefficient Total error Average resistance, compliance 0.79 326.85 Segmental resistance, compliance 0.91 251.86 Sliding Window Average 0.93 230.54

[0079] If segmented calculation is not used, the average correlation of the calculation results using a single average resistance and compliance is 0.797, and the average error is 326.85, which has a certain effect.

[0080] The average correlation calculated using segmental resistance and compliance was 0.91, and the average error was 251.86;

[0081] Combined with the results of sliding window averaging, the average correlation is 0.93, the average error is 230.54, and the final error is reduced by 30% and 8% compared with the non-segmented and segmented calculations, respectively. The correlation is increased by 0.13 and 0.02 compared with the non-segmented and segmented calculations, respectively.

[0082] The present invention is a method for calculating a spontaneous breathing effort curve based on a ventilator airway pressure and flow rate waveform. In the embodiment, the average resistance and compliance during several breaths are calculated, and the resistance and compliance of these breaths are also calculated in segments and the sliding window average is calculated. For each breath, three sets of data on resistance compliance changes over time are obtained. Based on these sets of resistance and compliance data, the inhalation effort data under different resistance compliance data are calculated. The calculated inhalation effort is then compared with the esophageal pressure used as a reference. The present invention is generally applicable to different ventilator waveforms.

[0083] Based on the above data, it can be concluded that when using average resistance and compliance to calculate inspiratory effort, the calculated results have a moderate correlation with the esophageal pressure used as a reference value.

[0084] After using the method proposed in the present invention for segmented calculation, the accuracy of the calculation results is high, the correlation coefficient has been greatly improved, and the total error value has been significantly reduced. After using the sliding window average, the evaluation indicators such as the correlation coefficient and the total error level have been further improved. The final results show that based on the ventilator airway pressure and flow rate, the resistance and compliance are calculated using the segmented calculation and sliding window average method, and the inspiratory effort calculated in this way has high accuracy and certain feasibility.

[0085] Corresponding to the aforementioned embodiment of a method for obtaining a spontaneous breathing effort curve under mechanical ventilation based on a ventilator waveform, the present invention further provides a method for monitoring the spontaneous breathing effort of a patient under mechanical ventilation, which is characterized in that:

[0086] The method for obtaining a spontaneous breathing effort curve under mechanical ventilation based on a ventilator waveform is used in real time to obtain a patient's spontaneous breathing effort curve under mechanical ventilation, and monitor the patient's spontaneous breathing effort.

[0087] The present invention also provides an electronic device, comprising one or more processors, for implementing a method for obtaining a spontaneous breathing effort curve under mechanical ventilation based on a ventilator waveform in the above-mentioned embodiment or a method for monitoring the spontaneous breathing effort of a patient under mechanical ventilation.

[0088] The electronic device of the present invention may be used in any device with data processing capability, and the device with data processing capability may be a device or apparatus such as a computer.

[0089] The device embodiment can be implemented by software, hardware or a combination of software and hardware. Taking software implementation as an example, as a device in a logical sense, it is formed by the processor of any device with data processing capability in which it is located to read the corresponding computer program instructions in the non-volatile memory into the memory for execution. From the hardware level, it includes a processor, memory, network interface, and non-volatile memory. In addition, any device with data processing capability in which the device in the embodiment is located can also include other hardware according to the actual function of the device with data processing capability, which will not be described in detail.

[0090] The implementation process of the functions and effects of each unit in the above-mentioned device is specifically described in the implementation process of the corresponding steps in the above-mentioned method, and will not be repeated here.

[0091] For the device embodiment, since it basically corresponds to the method embodiment, the relevant parts can refer to the partial description of the method embodiment. The device embodiment described above is only schematic, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of the present invention. Ordinary technicians in this field can understand and implement it without paying creative work.

[0092] An embodiment of the present invention also provides a computer-readable storage medium having a program stored thereon. When the program is executed by a processor, it implements a method for obtaining a spontaneous breathing effort curve under mechanical ventilation based on a ventilator waveform in the above-mentioned embodiment or a method for monitoring the spontaneous breathing effort of a patient under mechanical ventilation.

[0093] The computer-readable storage medium may be an internal storage unit of any device with data processing capability described in any of the aforementioned embodiments, such as a hard disk or a memory. The computer-readable storage medium may also be any device with data processing capability, such as a plug-in hard disk, a smart media card (SMC), an SD card, a flash card, etc. equipped on the device. Furthermore, the computer-readable storage medium may also include both an internal storage unit of any device with data processing capability and an external storage device. The computer-readable storage medium is used to store the computer program and other programs and data required by any device with data processing capability, and may also be used to temporarily store data that has been output or is to be output.

[0094] The contents described in the embodiments of this specification are merely enumerations of implementation forms of the inventive concept and are for illustrative purposes only. The protection scope of the present invention should not be considered to be limited to the specific forms described in this embodiment, and the protection scope of the present invention also extends to equivalent technical means that can be thought of by ordinary technicians in this field based on the inventive concept.

Claims

1. A method for obtaining a spontaneous breathing effort curve under mechanical ventilation based on a ventilator waveform, characterized in that: include: Obtain the patient's ventilator waveform data and airway pressure data under mechanical ventilation; Based on the acquired ventilator waveform data, calculate the resistance and compliance of the patient's respiratory system at each time point; Based on the acquired ventilator waveform data, airway pressure data and the calculated resistance and compliance of the patient's respiratory system at each time point, the inspiratory effort at each time point is calculated using an inspiratory effort formula constructed based on a circuit model of the respiratory system, thereby obtaining the patient's spontaneous respiratory effort curve under mechanical ventilation; wherein, the inspiratory effort formula constructed based on the circuit model of the respiratory system is expressed as follows: Where P mus For the patient's inspiratory effort, P aw is the patient's airway pressure, V is the flow rate of the airflow, and the integral of the flow rate over time is the tidal volume, R r and C r are the resistance and compliance of the patient's respiratory system, respectively.

2. The method according to claim 1, characterized in that The ventilator waveform data includes flow rate-time signal, pressure-time signal and tidal volume-time signal.

3. The method according to claim 1, characterized in that In the calculation of the resistance and compliance of the patient's respiratory system at each time point, the average resistance and average compliance of the patient's respiratory system for each breath are calculated as the resistance and compliance at each time point of the breath.

4. The method according to claim 1, characterized in that: In the calculation of the resistance and compliance of the patient's respiratory system at each time point, each breath is divided into the following four stages according to the changes in airway pressure and flow rate: pressure rising stage, pressure stable stage, pressure falling stage and end-of-breathing stage; The average resistance and average compliance of the patient's respiratory system at each stage of each breath are calculated as the resistance and compliance at each time point in the corresponding stage of the breath.

5. The method according to claim 4, characterized in that The average resistance and average compliance are calculated using the following formula in the end-of-breathing stage: Where d(sumV) represents the change in tidal volume at the end of breathing, and d(P) represents the change in pressure at the end of breathing. P=P aw , d(V) represents the change in flow velocity during the end-breathing phase.

6. The method according to claim 1, characterized in that After calculating the resistance and compliance of the patient's respiratory system at each time point, the resistance and compliance of the patient's respiratory system at each time point are smoothed.

7. The method according to claim 6, characterized in that The specific smoothing process is: In the curve composed of the resistance and compliance of the patient's respiratory system at each time point, the value at time s is adjusted to the average value of the data in the time period [sw:s+w] in sequence; where w is the sliding window length.

8. A method for monitoring the spontaneous breathing effort of a patient under mechanical ventilation, characterized in that: Specifically: The method for obtaining a spontaneous breathing effort curve under mechanical ventilation based on a ventilator waveform as described in any one of claims 1 to 7 is used in real time to obtain the patient's spontaneous breathing effort curve under mechanical ventilation, and monitor the patient's spontaneous breathing effort.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, a method for obtaining a spontaneous breathing effort curve under mechanical ventilation based on a ventilator waveform as described in any one of claims 1 to 7 is implemented.

10. A storage medium comprising computer executable instructions, wherein when the computer executable instructions are executed by a computer processor, the method for calculating a spontaneous breathing effort curve under mechanical ventilation based on a ventilator waveform as described in any one of claims 1 to 7 is implemented.

Images