Inhalation triggering control method, system and ventilator

Abstract

The application discloses an inspiration triggering control method and system and a breathing machine. The method comprises the following steps: collecting and calculating corresponding respiratory airflow velocity waveform data according to respiratory detection data in a current respiratory cycle; analyzing and extracting signal features of the respiratory airflow velocity waveform data to construct an end-expiratory dynamic straight line; determining a respiratory flow rate sampling point set corresponding to the respiratory airflow velocity waveform data according to the end-expiratory dynamic straight line; calculating distance values of each respiratory flow rate sampling point and the end-expiratory dynamic straight line respectively, and determining corresponding inspiration triggering points according to the distance values. The method can monitor respiratory transformation in real time, improve the accuracy, reliability and self-adaptability of inspiration triggering, and has high intelligent degree. Meanwhile, the method can also ensure human-machine synchronization, dynamically adjust the inspiration triggering point, and improve the experience effect of users.

Description

Technical Field

[0001] This invention relates to the field of medical device technology, and in particular to an inspiratory trigger control method, system and ventilator. Background Technology

[0002] In the field of medical device technology, ventilators are a common type of medical equipment. Human-ventilator coordination is a crucial factor affecting the effectiveness of ventilator-assisted breathing. The synchronization of the ventilator's respiratory triggering during spontaneous breathing is one manifestation of human-ventilator coordination. Currently, the most common respiratory triggering methods are pressure triggering and flow triggering.

[0003] Flow-triggered algorithms include zero-crossing detection triggering, flow threshold-based triggering, and signal pattern transformation-based triggering. These methods offer advantages such as short trigger delays, minimal pressure drops, and lower required triggering power for the user, making them more widely and frequently used in clinical practice. However, due to interference from air leaks and airway obstruction, they are prone to lag or advance of the expiratory phase, leading to false triggering or no triggering during inspiration. This, in turn, affects human-ventilator synchronization and reduces the user experience. Therefore, existing inspiratory triggering methods exhibit poor adaptability and robustness. Summary of the Invention

[0004] One of the objectives of this invention is to provide an inspiratory trigger control method to solve the technical problem in the prior art that the inspiratory trigger recognition deviation caused by air leakage or other interference of the ventilator is difficult to resolve, and that inspiratory triggering is prone to being too early or too late.

[0005] One of the objectives of this invention is to provide an inhalation trigger control system.

[0006] One of the objectives of this invention is to provide a ventilator.

[0007] To achieve one of the above-mentioned objectives, the present invention provides an inspiratory trigger control method, comprising: acquiring and calculating corresponding respiratory airflow velocity waveform data based on respiratory detection data within the current respiratory cycle; parsing and extracting signal features from the respiratory airflow velocity waveform data to construct an end-expiratory dynamic straight line; determining a set of respiratory velocity sampling points corresponding to the respiratory airflow velocity waveform data based on the end-expiratory dynamic straight line; calculating the distance between each respiratory velocity sampling point and the end-expiratory dynamic straight line, and determining the corresponding inspiratory trigger point based on the distance value.

[0008] As a further improvement of one embodiment of the present invention, the end-expiratory dynamic linear curve represents the change in respiratory airflow velocity at the end of the expiratory phase within a unit respiratory cycle.

[0009] As a further improvement of one embodiment of the present invention, the step of "collecting and calculating the corresponding respiratory airflow velocity waveform data based on the respiratory detection data within the current respiratory cycle" specifically includes: the control signal acquisition device collecting respiratory gas flow data and airway pressure data at the ventilator mask end within the current unit respiratory cycle, and performing data processing operations on the respiratory detection data to filter out effective respiratory gas flow data and effective airway pressure data; wherein, the data processing operations include at least one of respiratory signal conversion operations and respiratory signal filtering operations; and the respiratory airflow velocity waveform data is calculated based on the effective respiratory gas flow data and the effective airway pressure data.

[0010] As a further improvement of one embodiment of the present invention, the respiratory gas flow data includes the respiratory airflow velocity and the leakage rate at the ventilator mask end.

[0011] As a further improvement of one embodiment of the present invention, the step of "calculating the respiratory airflow velocity waveform data based on the respiratory gas flow data and the airway pressure data" specifically includes: acquiring and collecting several sets of respiratory gas flow data and corresponding airway pressure data within the current respiratory cycle according to the sampling frequency; calculating several gas leakage velocities corresponding to the ventilator mask end based on each set of airway pressure data; wherein, the gas leakage velocity is equal to the product of the leakage coefficient and the respiratory pressure data; the leakage coefficient is the quotient of the average value of the respiratory gas flow rate within the unit time buffer sliding window and the average value of the square root of the airway pressure; calculating several corresponding respiratory airflow velocities based on each set of respiratory gas flow data and the corresponding gas leakage velocity; wherein, the respiratory airflow velocity is equal to the difference between the respiratory gas flow data and the gas leakage velocity; and generating the corresponding respiratory airflow velocity waveform data using a data fitting method based on the several respiratory airflow velocities.

[0012] As a further improvement of one embodiment of the present invention, the step of "analyzing and extracting the signal features of the respiratory airflow velocity waveform data and constructing the end-expiratory dynamic straight line" specifically includes: acquiring historical respiratory airflow waveform data of several historical respiratory cycles, analyzing the signal features of the historical respiratory airflow waveform data, and determining a first reference point within the current respiratory cycle; analyzing the signal features of the respiratory airflow velocity waveform data, and determining a second reference point within the current respiratory cycle; and constructing the end-expiratory dynamic straight line based on the first reference point and the second reference point; wherein the first reference point and the second reference point represent the start and end points of the respiratory phase entering the end-expiratory stage within a unit respiratory cycle.

[0013] As a further improvement of one embodiment of the present invention, the step of "acquiring historical respiratory airflow waveform data of several historical respiratory cycles, analyzing the signal characteristics of the historical respiratory airflow waveform data, and determining the first reference point in the current respiratory cycle" specifically includes: acquiring historical respiratory airflow waveform data of several historical respiratory cycles prior to the current respiratory cycle in a preset quantity; extracting and calculating the average value of the minimum airflow velocity in each historical respiratory cycle based on the historical respiratory airflow waveform data to obtain the average respiratory flow velocity value; calculating the corresponding respiratory flow velocity amplitude based on the average respiratory flow velocity value; wherein the respiratory flow velocity amplitude is equal to the product of the average respiratory flow velocity value and a preset coefficient threshold; determining the index position of the respiratory flow velocity amplitude in the respiratory airflow waveform data of the current respiratory cycle based on a sliding window of sampling point time, and forming the first reference point based on the index position and the respiratory flow velocity amplitude.

[0014] As a further improvement of one embodiment of the present invention, the step of "analyzing the signal characteristics of the respiratory airflow velocity waveform data and determining the second reference point within the current respiratory cycle" specifically includes: setting an end-expiratory baseline; wherein the respiratory airflow velocity corresponding to the end-expiratory baseline is 0; determining the first intersection point position of the end-expiratory baseline and the respiratory airflow velocity waveform data based on a sliding window of sampling point time to form the second reference point; wherein the horizontal coordinate of the second reference point is the index value corresponding to the first intersection point position, and the vertical coordinate is 0.

[0015] As a further improvement of one embodiment of the present invention, the step of "determining the set of respiratory flow velocity sampling points corresponding to the respiratory airflow velocity waveform data based on the end-expiratory dynamic straight line" specifically includes: setting and determining the first intersection point position of the end-expiratory baseline and the respiratory airflow velocity waveform data; obtaining a number of sampling points corresponding to the respiratory airflow velocity waveform data that are greater than 0 after the first intersection point position with a preset number of sampling points, thereby forming the set of respiratory flow velocity sampling points.

[0016] As a further improvement of one embodiment of the present invention, the step of "calculating the distance between each respiratory flow sampling point and the end-expiratory dynamic straight line, and determining the corresponding inspiratory trigger point based on the distance value" specifically includes: calculating the distance between each respiratory flow sampling point and the end-expiratory dynamic straight line, and taking the respiratory flow sampling point corresponding to the maximum distance value as the undetermined inspiratory trigger point; setting and determining whether the undetermined inspiratory trigger point is the inspiratory trigger point based on the number of intersections between the end-expiratory baseline and the respiratory airflow velocity waveform data.

[0017] As a further improvement of one embodiment of the present invention, the step of "calculating the distance between each respiratory flow sampling point and the end-expiratory dynamic straight line, and determining the corresponding inspiratory trigger point based on the distance value" specifically includes: calculating and obtaining several corresponding triangle areas based on the distance between each respiratory flow sampling point and the end-expiratory dynamic straight line, and taking the respiratory flow sampling point corresponding to the largest triangle area as the undetermined inspiratory trigger point; setting and determining whether the undetermined inspiratory trigger point is the inspiratory trigger point based on the number of intersections between the end-expiratory baseline and the respiratory airflow velocity waveform data.

[0018] As a further improvement of one embodiment of the present invention, the step of "setting and determining whether the pending inspiratory trigger point is the inspiratory trigger point based on the number of intersections between the end-expiratory baseline and the respiratory airflow velocity waveform data" specifically includes: determining whether the number of intersections between the end-expiratory baseline and the respiratory airflow velocity waveform data is greater than 1; if so, determining whether the distance values ​​of several respiratory flow velocity sampling points after the pending inspiratory trigger point are monotonically decreasing; if so, determining the pending inspiratory trigger point as the inspiratory trigger point of the current respiratory cycle.

[0019] As a further improvement of one embodiment of the present invention, the step of "setting and determining whether the pending inspiratory trigger point is the inspiratory trigger point based on the number of intersections between the end-expiratory baseline and the respiratory airflow velocity waveform data" specifically includes: determining whether the number of intersections between the end-expiratory baseline and the respiratory airflow velocity waveform data is equal to 1; if so, determining whether the distance values ​​of several respiratory flow velocity sampling points after the pending inspiratory trigger point are monotonically increasing; if so, determining whether the respiratory airflow velocity corresponding to the pending inspiratory trigger point is greater than or equal to a preset airflow velocity threshold; if the respiratory airflow velocity corresponding to the pending inspiratory trigger point is greater than or equal to the preset airflow velocity threshold, determining that the pending inspiratory trigger point is the inspiratory trigger point of the current respiratory cycle; if the respiratory airflow velocity corresponding to the pending inspiratory trigger point is less than the preset airflow velocity threshold, controlling the ventilator not to trigger the inspiratory mode in the current respiratory cycle.

[0020] As a further improvement of one embodiment of the present invention, after "determining the corresponding inspiratory trigger point according to the distance value", the method further includes: acquiring and fitting an inspiratory trigger sensitivity curve based on several inspiratory trigger points and several gas leakage rates within several respiratory cycles; dynamically adjusting the inspiratory trigger point of the current respiratory cycle according to the inspiratory trigger sensitivity curve; wherein, the inspiratory trigger sensitivity curve is a quadratic curve with the gas leakage rate at the ventilator mask end as the independent variable and the inspiratory trigger sensitivity as the dependent variable.

[0021] To achieve one of the above-mentioned objectives, one embodiment of the present invention provides an inspiratory trigger control system, comprising: a data acquisition unit for acquiring respiratory gas flow rate data and airway pressure data within a unit respiratory cycle; a data preprocessing unit for filtering the acquired respiratory gas flow rate data and airway pressure data to obtain effective respiratory gas flow rate data and effective airway pressure data; a respiratory waveform signal extraction unit for calculating the gas leakage rate and respiratory airflow velocity waveform data at the ventilator mask end based on the effective respiratory gas flow rate data and the effective airway pressure data; and an inspiratory trigger detection unit for parsing and extracting the signal features of the respiratory airflow velocity waveform data to construct an end-expiratory dynamic straight line; for determining a set of respiratory velocity sampling points corresponding to the respiratory airflow velocity waveform data based on the end-expiratory dynamic straight line; and for calculating the distance value between each respiratory velocity sampling point and the end-expiratory dynamic straight line, and determining the corresponding inspiratory trigger point based on the distance value.

[0022] To achieve one of the above-mentioned objectives, one embodiment of the present invention provides a ventilator, comprising: a memory and a processor, wherein the memory has a computer program that can run on the processor, and the processor executes the program to implement the steps of any of the above-described inspiratory trigger control methods.

[0023] Compared with the prior art, the embodiments of the present invention have at least one of the following beneficial effects:

[0024] This invention employs an inspiratory trigger control method. By calculating and analyzing real-time respiratory airflow velocity data, a dynamic straight line at the end of the breath is constructed. This eliminates interference from respiratory airflow velocity caused by air leakage, and more accurately displays the changes in respiratory airflow velocity within a unit respiratory cycle. Furthermore, by calculating the distance between the respiratory airflow velocity sampling point and the dynamic straight line at the end of the breath, respiratory changes can be monitored in real time, improving the accuracy, reliability, and adaptability of inspiratory triggering, resulting in a high degree of intelligence. At the same time, it can also ensure human-machine synchronization, dynamically adjust the inspiratory trigger point, and improve the user experience. Attached Figure Description

[0025] Figure 1 This is a schematic diagram of the intake trigger control system in one embodiment of the present invention.

[0026] Figure 2 This is a schematic diagram of the steps of an intake trigger control method according to an embodiment of the present invention.

[0027] Figure 3 This is a detailed schematic diagram of step S1 of the inhalation trigger control method in one embodiment of the present invention.

[0028] Figure 4This is a detailed schematic diagram of step S12 of the inhalation trigger control method in one embodiment of the present invention.

[0029] Figure 5(a) is a schematic diagram of the result of the inspiratory trigger point without interference during the respiratory cycle of the inspiratory trigger control method in one embodiment of the present invention.

[0030] Figure 5(b) is a schematic diagram of the maximum distance between the respiratory airflow waveform data and the dynamic straight line at the end of expiration having multiple intersection points in an inspiratory trigger control method according to an embodiment of the present invention.

[0031] Figure 5(c) is a schematic diagram showing the maximum distance between the respiratory airflow waveform data and the dynamic straight line at the end of expiration, which intersect at a point in an inspiratory trigger control method according to an embodiment of the present invention.

[0032] Figure 5(d) is a schematic diagram of the area of ​​a triangle with multiple intersection points between the respiratory airflow waveform data and the dynamic straight line at the end of expiration in an embodiment of the present invention.

[0033] Figure 6 This is a detailed schematic diagram of step S2 of the inhalation trigger control method in one embodiment of the present invention.

[0034] Figure 7(a) is a detailed schematic diagram of step S21 of the inhalation trigger control method in one embodiment of the present invention.

[0035] Figure 7(b) is a detailed schematic diagram of step S22 of the inhalation trigger control method in one embodiment of the present invention.

[0036] Figure 8 This is a schematic diagram of step S3 of the inhalation trigger control method in one embodiment of the present invention.

[0037] Figure 9(a) is a detailed schematic diagram of step S4 of the inhalation trigger control method in the first embodiment of the present invention.

[0038] Figure 9(b) is a detailed schematic diagram of step S4 of the inhalation trigger control method in the second embodiment of the present invention.

[0039] Figure 10 This is a flowchart illustrating a preferred embodiment of the inhalation trigger control method according to one aspect of the present invention. Detailed Implementation

[0040] The present invention will now be described in detail with reference to the specific embodiments shown in the accompanying drawings. However, these embodiments do not limit the present invention, and any structural, methodological, or functional modifications made by those skilled in the art based on these embodiments are included within the scope of protection of the present invention.

[0041] It should be noted that the term "comprising" or any other variations thereof is intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. In the description of specific embodiments of the present invention, the terms "first," "second," etc., are used for descriptive purposes only and should not be construed as indicating or implying relative importance.

[0042] Ventilators may experience inspiratory trigger recognition errors due to air leaks or other interference factors. This means that the detection of inspiratory triggers may be delayed or premature, causing a missynchronization between the user's inspiratory actions and the ventilator's inspiratory-to-weaning operations, leading to breathing discomfort. Therefore, accurately identifying the inspiratory trigger point within the respiratory cycle has significant clinical and scientific value in advancing medical science and improving user care.

[0043] Based on this, the present invention provides an inhalation trigger control system, such as... Figure 1 As shown, the inhalation trigger control system 500 may specifically include:

[0044] The data acquisition unit 10 can be used to acquire respiratory gas flow rate data and airway pressure data within a unit respiratory cycle. Specifically, in one embodiment, the data acquisition unit 10 can convert the acquired analog signals into corresponding digital signals, and the sampling frequency f s The frequency can be preferably set to 100Hz to 1000Hz, but other sampling frequencies are not excluded.

[0045] The data preprocessing unit 20 can be used to filter out noise from the collected respiratory gas flow data and airway pressure data to obtain effective respiratory gas flow data and effective airway pressure data. Specifically, in one embodiment, a filtering algorithm can be used to perform a filtering operation on the converted digital signal to obtain an effective respiratory signal. Optionally, the filtering algorithm can be a bandpass digital filter based on FIR (Finite Impulse Response) with a passband frequency set to 0.1Hz-0.5Hz. Of course, this invention does not exclude other filtering algorithms.

[0046] Optionally, the present invention may preferably employ two storage units with a storage length of 5*f. s The sliding windows respectively cache the filtered respiratory gas flow data and airway pressure data.

[0047] The respiratory waveform signal extraction unit 30 can be used to calculate the gas leakage rate and respiratory airflow rate waveform data at the ventilator mask end based on the effective respiratory gas flow rate data and the effective airway pressure data.

[0048] The inspiratory trigger detection unit 40 can be used for inspiratory trigger detection, leakage monitoring, and automatic adjustment of respiratory sensitivity. Specifically, it acquires and determines respiratory airflow velocity waveform data based on effective respiratory gas flow data and effective airway pressure data; constructs an end-expiratory dynamic straight line based on the respiratory airflow velocity waveform data, and determines a set of respiratory flow velocity sampling points corresponding to the respiratory airflow velocity waveform data based on the end-expiratory dynamic straight line; calculates the distance value between each respiratory flow velocity sampling point and the end-expiratory dynamic straight line, and determines the corresponding inspiratory trigger point based on the distance value.

[0049] Optionally, in a preferred embodiment, the inspiratory trigger detection unit 40 can obtain an inspiratory trigger sensitivity curve by acquiring and fitting several gas leakage rates corresponding to the several inspiratory trigger points; during the inspiratory triggering process, the inspiratory trigger point of the current respiratory cycle is dynamically adjusted according to the inspiratory trigger sensitivity curve.

[0050] Furthermore, the present invention also provides an inhalation trigger control method, such as... Figure 2 As shown, the breathing gas triggering control method specifically includes the following steps:

[0051] Step S1: Collect and calculate the corresponding respiratory airflow velocity waveform data based on the respiratory detection data within the current respiratory cycle;

[0052] Step S2: Analyze and extract the signal features of the respiratory airflow velocity waveform data to construct a dynamic straight line at the end of expiration;

[0053] Step S3: Based on the end-expiratory dynamic straight line, determine the set of respiratory velocity sampling points corresponding to the respiratory airflow velocity waveform data;

[0054] Step S4: Calculate the distance between each respiratory flow sampling point and the end-expiratory dynamic straight line, and determine the corresponding inspiratory trigger point based on the distance value.

[0055] Thus, by constructing a dynamic straight line at the end of the exhalation based on real-time respiratory airflow velocity data, interference from respiratory airflow velocity caused by air leakage can be eliminated, and the changes in respiratory airflow velocity within a unit respiratory cycle can be displayed more accurately. The inspiratory trigger point can be dynamically adjusted, with high accuracy, reliability, and strong adaptability.

[0056] The end-expiratory dynamic line characterizes the change in respiratory airflow velocity at the end of each respiratory cycle. In other words, the change in the end-expiratory dynamic line reveals the change in the user's respiratory airflow velocity within each respiratory cycle.

[0057] like Figure 3As shown, in one embodiment, the present invention provides a detailed step for step S1, which may specifically include:

[0058] Step S11: The control signal acquisition device collects respiratory gas flow data and airway pressure data at the ventilator mask end within the current unit respiratory cycle, and performs data processing operations on the respiratory detection data to filter out effective respiratory gas flow data and effective airway pressure data.

[0059] Step S12: Calculate the respiratory airflow velocity waveform data based on the effective respiratory gas flow rate data and the effective airway pressure data.

[0060] In this way, by collecting and processing changes in the user's respiratory gas flow and pressure data in real time, noise or other interference factors can be reduced, and the accuracy of respiratory airflow velocity waveform data can be improved.

[0061] The data processing operation may include at least one of a respiratory signal conversion operation and a respiratory signal filtering operation. Specifically, in one embodiment, a signal conversion operation is performed on the collected respiratory detection data; in another embodiment, a filtering operation is performed on the collected respiratory detection data; in a preferred embodiment, the two embodiments described above may be used in combination.

[0062] Furthermore, the respiratory gas flow data may include the respiratory airflow velocity and the leakage rate at the ventilator mask end. The respiratory airflow velocity refers to the speed at which respiratory gas flows during breathing; the leakage rate at the ventilator mask end refers to the rate at which gas leaks from the ventilator mask end due to factors such as mask size and the user's facial shape. Understandably, the leakage rate at the ventilator mask end may affect the real-time respiratory gas flow data within the current unit cycle.

[0063] Based on this, such as Figure 4 As shown, in one embodiment, step S12 may specifically include the following steps:

[0064] Step S121: Acquire and collect several sets of respiratory gas flow data and corresponding airway pressure data within the current respiratory cycle according to the sampling frequency;

[0065] Step S122: Calculate the gas leakage rates corresponding to the ventilator mask end based on each set of airway pressure data.

[0066] Step S123: Calculate the corresponding breathing airflow velocities based on each group of breathing gas flow data and the corresponding gas leakage rate.

[0067] Step S124: Based on the several respiratory airflow velocities, generate corresponding respiratory airflow velocity waveform data using a data fitting method.

[0068] In this way, by eliminating the gas leakage rate at the ventilator mask end, errors can be reduced, and more accurate respiratory gas flow data can be obtained, laying the foundation for subsequent calculation of the inspiratory trigger point.

[0069] Wherein, the gas leakage rate is equal to the product of the leakage coefficient and the breathing pressure data; the leakage coefficient is the quotient of the average breathing gas flow rate within the unit time buffer sliding window and the average value of the airway pressure (square root); the breathing airflow velocity is equal to the difference between the breathing gas flow rate data and the gas leakage rate.

[0070] It should be noted that the gas leakage rate at the ventilator mask end may include the total leakage rate and the instantaneous leakage rate. Specifically, since the collected respiratory gas flow rate data is the sum of the respiratory airflow velocity and the total leakage rate at the ventilator mask end, i.e., Q... totalflow =Q leak +Q resp , where Q totalflow Q represents the total respiratory gas flow rate data collected by the data acquisition unit during the current respiratory cycle. leak Q represents the total gas leakage rate at the ventilator mask during the current respiratory cycle. resp This represents the respiratory airflow velocity during the current respiratory cycle, from which we can determine the respiratory airflow velocity Q during the current respiratory cycle. resp =Q totalflow -Q leak Among them, Q leak It can be derived from the fluid dynamics equations To determine this, k represents the leakage coefficient, which can be a constant or a coefficient. This represents the average respiratory airflow velocity within a unit sliding window. This represents the average value of the airway pressure within a unit sliding window, expressed as the square root of the average value.

[0071] Based on this, the instantaneous leakage rate Q′ at the ventilator mask end can be calculated. leak =k*P, thus the corresponding instantaneous respiratory airflow velocity Q′ can be calculated. resp =Q′ totalflow -Q′ leak Understandably, Q′ totalflow It can represent instantaneous respiratory airflow rate data.

[0072] It should be noted that, based on the above description, respiratory signals are extracted and corresponding respiratory airflow velocity waveform data are generated according to several expiratory airflow velocities, as shown in Figure 5(a). From the waveform data in the figure, it can be seen intuitively that the end-expiratory inflection point in each respiratory cycle is the inspiratory trigger point. However, in reality, due to slight interference at the end of expiration, such as coughing, swallowing, airway obstruction, etc., the respiratory airflow velocity may change, which may also cause the inspiratory trigger point in the figure to deviate.

[0073] Based on this, such as Figure 6 As shown, in one embodiment, the present invention provides a detailed step for step S2, which may specifically include the following steps:

[0074] Step S21: Obtain historical respiratory airflow waveform data of several historical respiratory cycles, analyze the signal characteristics of the historical respiratory airflow waveform data, and determine the first reference point in the current respiratory cycle;

[0075] Step S22: Analyze the signal characteristics of the respiratory airflow velocity waveform data to determine the second reference point within the current respiratory cycle;

[0076] Step S23: Construct the end-expiratory dynamic straight line based on the first reference point and the second reference point.

[0077] Thus, by constructing a dynamic straight line at the end of expiration, the flow rate changes at the end of expiration can be accurately described, providing a reference benchmark for assessing the magnitude and trend of respiratory flow changes. This helps to analyze and identify the characteristics of the end of expiration and provides a reliable basis for subsequently determining the inspiratory trigger point.

[0078] The first reference point and the second reference point can represent the start and end points of the respiratory phase entering the end-expiratory stage within a unit respiratory cycle. Furthermore, steps S21 and S22 do not have a specific order; step S22 can be placed before step S21.

[0079] Furthermore, as shown in Figure 7(a), in one embodiment, step S21 may specifically include the following steps:

[0080] Step S211: Obtain historical respiratory flow waveform data for a number of historical respiratory cycles prior to the current respiratory cycle using a preset quantity;

[0081] Step S212: Based on the historical respiratory airflow waveform data, extract and calculate the average value of the minimum airflow velocity in each historical respiratory cycle to obtain the average respiratory flow velocity value;

[0082] Step S213: Calculate the corresponding respiratory flow amplitude based on the average respiratory flow value; wherein the respiratory flow amplitude is equal to the product of the average respiratory flow value and a preset coefficient threshold.

[0083] Step S214: Based on the sliding window of the sampling point time, determine the index position of the respiratory flow amplitude in the respiratory airflow waveform data of the current respiratory cycle, and form the first reference point according to the index position and the respiratory flow amplitude.

[0084] In this way, by calculating the average value of several historical respiratory airflow velocities, the occasional interference caused by a single respiratory cycle can be avoided, which helps to extract more stable and reliable signal features, making the determination of reference points more accurate and reliable.

[0085] The respiratory airflow velocity and respiratory gas flow rate are correlated; in other words, the greater the respiratory airflow velocity, the greater the corresponding respiratory gas flow rate. The preset quantity is preferably 3, meaning three historical respiratory cycles prior to the current respiratory cycle are acquired. The preset coefficient threshold can be based on the clinical definition of hypoventilation events, which can be defined as "a decrease of more than 30% in respiratory airflow intensity or amplitude during sleep compared to baseline levels." Therefore, the preset coefficient threshold is preferably 0.3. Of course, this invention does not exclude other preset quantities and preset coefficient thresholds, and no specific limitations are imposed here; they can be adjusted according to actual conditions.

[0086] As shown in Figure 7(b), in another embodiment, step S22 may specifically include the following steps:

[0087] Step S221, set the end-expiratory baseline;

[0088] Step S222: Based on the sliding window of the sampling point time, determine the first intersection point of the end-expiratory baseline and the respiratory airflow velocity waveform data to form the second reference point.

[0089] In this way, by using the end-expiratory baseline as a reference line, the position of the end-expiratory baseline can be adjusted according to different individuals and operating conditions, better adapting to individual changes and ensuring the accuracy and consistency of subsequent inspiratory trigger points.

[0090] Wherein, the respiratory airflow velocity corresponding to the end-expiratory baseline can all be 0; the x-coordinate of the second reference point can be the index value corresponding to the position of the first intersection point, and the y-coordinate is 0. It should be noted that, in the end-expiratory phase of the current respiratory cycle, there may be multiple intersection points between the end-expiratory baseline and the respiratory airflow velocity waveform data, and the second reference point can be the first intersection point.

[0091] Furthermore, the sliding window is based on a two-pointer concept, where a window is formed between the elements pointed to by the two pointers. In this invention, the sliding window for the sampling point time can be based on the time axis, selecting a continuous time period on the respiratory waveform data. The size of this time period is determined by the size of the sliding window; that is, the sliding window can be understood as a window that slides along the time axis. The abscissas of the first sampling point and the second sampling point can respectively represent the temporal positions of the first reference point and the second reference point in the respiratory waveform data.

[0092] For example, as shown in Figure 5(b), the minimum airflow velocity (i.e., the airflow velocity corresponding to the trough of the corresponding historical respiratory airflow waveform data) is extracted for each historical respiratory cycle, resulting in three historical minimum airflow velocities; the average of the three historical minimum airflow velocities is calculated as follows: Based on the clinical assessment of hypoventilation events, when the current respiratory phase is in the expiratory phase, the respiratory airflow velocity is judged to be continuously increasing to... Right now Determine the first reference point A. Within the current respiratory cycle, the first intersection point B of the end-expiratory baseline and the respiratory airflow velocity waveform data is designated as the second reference point.

[0093] The execution order of steps S211 to S214 and steps S221 to S222 is not important and will not affect the final result; they are merely labels used for the convenience of process description. In other words, steps S221 to S222 can be placed before steps S211 to S214 as a whole, or they can be interspersed among the steps.

[0094] Once the positions of the first and second reference points are determined, the slope of the end-expiratory dynamic line is also determined. This invention calculates and determines whether there exists a sampling point with the longest distance to the end-expiratory dynamic line within the set of respiratory flow sampling points after the second reference point.

[0095] Based on this, such as Figure 8 As shown, in one embodiment, the present invention provides a detailed step for step S3, which may specifically include the following steps:

[0096] Step S31: Set and determine the first intersection point of the end-expiratory baseline and the respiratory airflow velocity waveform data;

[0097] Step S32: Using a preset number of sampling points, obtain several sampling points corresponding to the respiratory airflow velocity waveform data that are greater than 0 after the first intersection point position, to form the respiratory velocity sampling point set.

[0098] Thus, by obtaining the set of respiratory flow sampling points after the first intersection, it is helpful to accurately describe the changing trend of airflow velocity in the initial stage of the respiratory cycle, providing accurate data support for the determination of subsequent inspiratory trigger points.

[0099] The preset number of sampling points is preferably 10, that is, after obtaining the position of the first intersection point, 10 sampling points corresponding to the respiratory airflow velocity greater than 0 on the respiratory airflow waveform data are used to form the respiratory velocity sampling point set, which can be denoted as X = {x1, x2, ..., x...} 10}, where x i Corresponding respiratory airflow velocity It can satisfy The unit corresponding to 0 is liters per second (Lpm).

[0100] Furthermore, selecting sampling points with a respiratory airflow velocity greater than 0 ensures that, under normal breathing conditions, the set of respiratory flow velocity sampling points corresponds to the inspiratory phase. Of course, the respiratory airflow velocity at the sampling points is not limited to being greater than 0 and can be adaptively adjusted according to individual differences. Therefore, any adaptive modifications made by those skilled in the art that do not depart from the concept of this invention are included within the scope of this invention.

[0101] As shown in Figure 9(a), in the first embodiment, the present invention provides a refined step for step S4, which may specifically include the following steps:

[0102] Step S411: Calculate the distance between each respiratory flow sampling point and the end-expiratory dynamic straight line, and take the respiratory flow sampling point corresponding to the maximum distance value as the undetermined inspiratory trigger point;

[0103] Step S412: Set and determine whether the pending inspiratory trigger point is the inspiratory trigger point based on the number of intersections between the end-expiratory baseline and the respiratory airflow velocity waveform data.

[0104] Thus, calculating and determining the inhalation trigger point based solely on the maximum distance value is a simple and easy-to-implement method. Furthermore, by comprehensively considering both the distance value and the number of intersection points, the accuracy and stability of the inhalation trigger point can be evaluated more comprehensively.

[0105] As shown in Figure 9(b), in the second embodiment, the present invention provides a refined step for step S4, which may specifically include the following steps:

[0106] Step S421: Calculate the area of ​​several corresponding triangles based on the distance between each respiratory flow sampling point and the end-expiratory dynamic straight line, and take the respiratory flow sampling point corresponding to the largest triangle area as the undetermined inspiratory trigger point.

[0107] Step S422: Set and determine whether the pending inspiratory trigger point is the inspiratory trigger point based on the number of intersections between the end-expiratory baseline and the respiratory airflow velocity waveform data.

[0108] In this way, by calculating the area between the sampling point and the end-expiratory dynamics, it is less susceptible to noise interference, can better represent respiratory signal characteristics, and improve the robustness and reliability of the algorithm.

[0109] To eliminate fluctuations in respiratory flow rate caused by external interference (such as coughing, swallowing, etc.), the distance values ​​or triangle areas of several sampling points after the undetermined inspiratory trigger point are judged to determine whether flow fluctuations or flow rebound occur. Specifically, this can be described based on the number of intersections between the end-expiratory baseline and the respiratory airflow velocity waveform data.

[0110] Based on this, in one embodiment, step S412 may specifically include the following steps:

[0111] Step S41211: Determine whether the number of intersections between the end-expiratory baseline and the respiratory airflow velocity waveform data is greater than 1;

[0112] If so, proceed to step S41212 to determine whether the distance values ​​of several respiratory flow sampling points after the undetermined inhalation trigger point are monotonically decreasing.

[0113] If so, proceed to step S41213 to determine the pending inspiratory trigger point as the inspiratory trigger point of the current respiratory cycle.

[0114] In this way, it can be dynamically adjusted according to the number of intersections, which can better adapt to the differences between different individuals, exhibiting strong adaptability, reducing human intervention, improving automation and efficiency, and also providing more effective and reliable results for determining the inhalation trigger point.

[0115] Specifically, in one implementation, when the end-expiratory dynamic straight line intersects with the respiratory airflow velocity waveform data at multiple points, referring to Figure 5(b), a sliding window D = {d1, d2, ..., d...} with a length of 10 sampling points can be pre-set. 10 The time duration is approximately 50ms, and the sliding window can be used to cache and calculate sampling points x in the set of respiratory flow sampling points in real time. i The distance d to the end-expiratory dynamic line (i.e., line AB in the figure) i This distance value can be calculated using Heron's formula, where the distance value d i ∈D. Calculate and determine the distance value d within the sliding window. i The size change characteristics can specifically include: judging the slope change trend of the sliding window D, if the distance value d iIt is constantly decreasing, as the distance value d i If the slope between adjacent points within the detection buffer sliding window decreases for 10 consecutive times (i.e., the slope value is negative for 10 consecutive times), then inspiration is triggered, and the inspiration trigger point is the first coordinate point of the sliding window. In other words, if the distance d1 is the largest, then the respiratory flow sampling point corresponding to d1 is the undetermined inspiration trigger point; the distance from d1 to d2 is determined by comparison. 10 Since it is monotonically decreasing, we can determine that the respiratory flow sampling point corresponding to d1 is the inspiratory trigger point Y in the current respiratory cycle.

[0116] In another embodiment, step S412 may specifically include the following steps:

[0117] Step S41221: Determine whether the number of intersections between the end-expiratory baseline and the respiratory airflow velocity waveform data is equal to 1;

[0118] If so, proceed to step S41222 to determine whether the distance values ​​of several respiratory flow sampling points after the undetermined inhalation trigger point are monotonically increasing;

[0119] If so, proceed to step S41223 to determine whether the breathing airflow velocity corresponding to the pending inhalation trigger point is greater than or equal to a preset airflow velocity threshold.

[0120] Step S41224: If the respiratory airflow velocity corresponding to the pending inspiratory trigger point is greater than or equal to the preset airflow velocity threshold, then the pending inspiratory trigger point is determined to be the inspiratory trigger point of the current respiratory cycle.

[0121] Step S41225: If the respiratory airflow velocity corresponding to the pending inspiratory trigger point is less than the preset airflow velocity threshold, then the ventilator is controlled not to trigger the inspiratory mode in the current respiratory cycle.

[0122] In this way, it can be dynamically adjusted according to the number of intersections, which can better adapt to the differences between different individuals, exhibiting strong adaptability, reducing human intervention, improving automation and efficiency, and also providing more effective and reliable results for determining the inhalation trigger point.

[0123] Specifically, when the end-expiratory dynamic straight line intersects the respiratory airflow velocity waveform data at one point, as shown in Figure 5(c), the distance value d within the sliding window is calculated and determined. i It increases gradually. Due to individual differences, some individuals may exhibit different respiratory flow velocity waveforms at the first reference point A, the second reference point B, and the respiratory flow velocity sampling point x. i To better distinguish these points and improve the accuracy of judgment on a straight line with nearly the same slope, the respiratory airflow velocity corresponding to the undetermined inspiratory trigger point can be used. Further restrictions are made to ensure that it meets the requirements. Here, 2 corresponds to the unit liters per second (Lpm). In other words, the respiratory flow sampling point with the largest distance value in the sliding window and a corresponding respiratory airflow velocity greater than or equal to 2Lpm is selected as the inspiratory trigger point Y in the current respiratory cycle.

[0124] Similarly, as shown in Figure 5(d), in one embodiment, the present invention can also determine the inspiratory trigger point by calculating the maximum triangle area of ​​the undetermined inspiratory trigger point and the dynamic line AB at the end of expiration. Specifically, this may include: when the dynamic line at the end of expiration intersects with the respiratory airflow velocity waveform data at multiple points, calculating the triangle area S = {S1, S2, ..., S...} formed by each respiratory flow velocity sampling point and the line AB. 10 If the area of ​​the triangle is S i As the area S of the triangle decreases, i If the slope changes negative 10 times consecutively (i.e., the slope change between adjacent points within the detection buffer sliding window is negative 10 times consecutively), then an inhalation trigger is initiated, with the inhalation trigger point being the first coordinate point of the sliding window. When the end-expiratory dynamic straight line intersects the respiratory airflow velocity waveform data at one point, refer to the distance value described in Figure 5(c) above, which will not be elaborated upon here.

[0125] It should be noted that the inspiratory trigger control method described above can be applied to a single respiratory cycle or to multiple respiratory cycles separately. In other words, the inspiratory trigger point for each respiratory cycle can dynamically change according to the real-time respiratory airflow rate of the current respiratory cycle. Optionally, the present invention can also use the inspiratory trigger control method described above to modify existing inspiratory trigger points, thereby improving the accuracy and reliability of inspiratory triggering.

[0126] The execution order of steps S411 to S412 and steps S421 to S422 is not important and will not affect the final result. Similarly, the execution order of steps S41211 to S41213 and steps S41221 to S41225 is also not important. Here, they are merely labels used for the convenience of process description. In other words, steps S421 to S422 can be placed before steps S411 to S412 as a whole, or they can be executed intermittently; steps S41221 to S41225 can be placed before steps S41211 to S41213 as a whole, or they can be executed intermittently.

[0127] To address different sensitivities to inspiratory triggering and respiratory phase switching, different quantitative thresholds can be added after determining the inspiratory trigger point within the current respiratory cycle, allowing for the setting of different levels of inspiratory trigger sensitivity. However, given that different individuals experience varying degrees of gas leakage, this may lead to varying degrees of inspiratory trigger delay. Therefore, this invention can automatically adjust the inspiratory trigger sensitivity based on different gas leakage rates.

[0128] Accordingly, in one embodiment, the inhalation trigger control method may further include the following steps:

[0129] Step S51: Obtain and fit the inspiratory trigger sensitivity curve based on several inspiratory trigger points and several gas leakage rates within several respiratory cycles.

[0130] Step S52: Dynamically adjust the inspiratory trigger point of the current respiratory cycle according to the inspiratory trigger sensitivity curve.

[0131] In this way, the intake trigger sensitivity can be adaptively adjusted according to different leakage rates, resulting in a high degree of automation and strong reliability.

[0132] The inspiratory trigger sensitivity curve is a quadratic curve with the gas leakage rate at the ventilator mask end as the independent variable and the inspiratory trigger sensitivity as the dependent variable. A regression model can be fitted based on the principle of least squares, according to the correspondence between the interval distribution of gas leakage rate and different inspiratory trigger sensitivities. The correspondence between gas leakage rate and different trigger sensitivities is as follows: the higher the gas leakage rate, the higher the corresponding inspiratory trigger sensitivity; the lower the gas leakage rate, the lower the corresponding inspiratory trigger sensitivity.

[0133] Optionally, in one embodiment, the inhalation trigger sensitivity curve can at least satisfy: S = a * Q 2 leak +b*Q leak +c; where S represents the inspiratory trigger sensitivity, Q leak The value represents the gas leakage rate at the ventilator mask end, and a, b, and c represent the parameters of the fitted curve. Of course, this invention does not exclude regression curves generated by other fitting methods.

[0134] like Figure 10 A flowchart illustrating an inhalation trigger control method in a preferred embodiment is shown below. Figure 10 The processing procedure of this preferred embodiment is summarized below.

[0135] Collect respiratory gas flow rate and airway pressure data within a single respiratory cycle;

[0136] The respiratory gas flow rate data and the airway pressure data are preprocessed to calculate the respiratory airflow velocity, gas leakage velocity and respiratory airflow velocity waveform data.

[0137] Analyze and extract the signal features of the respiratory airflow velocity waveform data to construct a dynamic straight line at the end of expiration;

[0138] Based on the end-expiratory dynamic line, the inspiratory trigger point within the current respiratory cycle is determined by calculating and determining the distance between each respiratory flow sampling point and the end-expiratory dynamic line.

[0139] The present invention also provides a ventilator, comprising: a memory and a processor, wherein the memory has a computer program that can run on the processor, and the processor executes the program to implement the above-described inspiratory trigger control method.

[0140] In summary, the inspiratory trigger control method provided by this invention determines the undetermined inspiratory trigger point based on the maximum distance between the adaptively adjusted end-expiratory dynamic straight line and the set of respiratory flow sampling points, exhibiting good robustness. Furthermore, it determines the final inspiratory trigger point based on the number of intersections between the end-expiratory baseline and the respiratory airflow velocity waveform data, and the changing trends of several respiratory flow sampling points after the undetermined inspiratory trigger point. This effectively reduces the premature or delayed inspiratory triggering caused by end-expiratory leakage and other interferences, improving the accuracy and reliability of inspiratory trigger judgment. In addition, it automatically adjusts the inspiratory trigger sensitivity according to different gas leakage rates, reducing manual intervention, improving the level of intelligence and human-machine synchronization, and enhancing the user's comfort experience.

[0141] It should be understood that although this specification describes embodiments, not every embodiment contains only one independent technical solution. This way of describing the specification is only for clarity. Those skilled in the art should regard the specification as a whole. The technical solutions in each embodiment can also be appropriately combined to form other embodiments that can be understood by those skilled in the art.

[0142] The detailed descriptions listed above are merely specific descriptions of feasible embodiments of the present invention, and are not intended to limit the scope of protection of the present invention. All equivalent embodiments or modifications made without departing from the spirit of the present invention should be included within the scope of protection of the present invention.

Claims

1. An inspiratory triggering control system, the control system being used to execute a respiratory triggering control method, characterized in that, include: Collect and calculate the corresponding respiratory airflow velocity waveform data based on the respiratory detection data within the current respiratory cycle; Analyze and extract the signal features of the respiratory airflow velocity waveform data to construct a dynamic straight line at the end of expiration; Based on the end-expiratory dynamic line, a set of respiratory flow velocity sampling points corresponding to the respiratory airflow velocity waveform data is determined; the end-expiratory dynamic line characterizes the change in respiratory airflow velocity at the end of a unit respiratory cycle. Calculate the distance between each respiratory flow sampling point and the end-expiratory dynamic straight line, and determine the corresponding inspiratory trigger point based on the distance value.

2. The inhalation trigger control system according to claim 1, characterized in that, The phrase "collecting and calculating the corresponding respiratory airflow velocity waveform data based on respiratory detection data within the current respiratory cycle" specifically includes: Within the current respiratory cycle, the control signal acquisition device acquires respiratory gas flow data and airway pressure data from the ventilator mask, and performs data processing operations on the respiratory detection data to filter out effective respiratory gas flow data and effective airway pressure data; wherein, the data processing operations include at least one of respiratory signal conversion operations and respiratory signal filtering operations; The respiratory airflow velocity waveform data is calculated based on the effective respiratory gas flow rate data and the effective airway pressure data.

3. The inhalation triggering control system according to claim 2, characterized in that, The respiratory gas flow data includes the respiratory airflow velocity and the leakage rate at the ventilator mask end.

4. The inhalation triggering control system according to claim 2, characterized in that, The phrase "calculating the respiratory airflow velocity waveform data based on the respiratory gas flow rate data and the airway pressure data" specifically includes: Acquire and collect several sets of respiratory gas flow data and corresponding airway pressure data within the current respiratory cycle according to the sampling frequency; Based on each set of airway pressure data, several gas leakage rates corresponding to the ventilator mask are calculated; wherein, the gas leakage rate is equal to the product of the leakage coefficient and the airway pressure data; the leakage coefficient is the quotient of the average respiratory gas flow rate within the buffer sliding window per unit time and the square root of the average airway pressure. Based on each set of respiratory gas flow rate data and the corresponding gas leakage rate, several corresponding respiratory airflow velocities are calculated; wherein, the respiratory airflow velocity is equal to the difference between the respiratory gas flow rate data and the gas leakage rate; Based on the aforementioned respiratory airflow velocities, a data fitting method is used to generate corresponding respiratory airflow velocity waveform data.

5. The inhalation triggering control system according to claim 1, characterized in that, The phrase "analyzing and extracting the signal features of the respiratory airflow velocity waveform data to construct a dynamic straight line at the end of expiration" specifically includes: Acquire historical respiratory airflow waveform data from several historical respiratory cycles, analyze the signal characteristics of the historical respiratory airflow waveform data, and determine the first reference point within the current respiratory cycle; Analyze the signal characteristics of the respiratory airflow velocity waveform data to determine the second reference point within the current respiratory cycle; The end-expiratory dynamic straight line is constructed based on the first reference point and the second reference point; wherein the first reference point and the second reference point represent the start and end points of the respiratory phase entering the end-expiratory stage within a unit respiratory cycle.

6. The inhalation triggering control system according to claim 5, characterized in that, The phrase "acquiring historical respiratory airflow waveform data from several historical respiratory cycles, analyzing the signal characteristics of the historical respiratory airflow waveform data, and determining the first reference point within the current respiratory cycle" specifically includes: Acquire historical respiratory flow waveform data from several previous respiratory cycles prior to the current respiratory cycle using a preset quantity; Based on the historical respiratory airflow waveform data, the average value of the minimum airflow velocity in each historical respiratory cycle is extracted and calculated to obtain the average respiratory flow rate value; Based on the average respiratory flow rate value, the corresponding respiratory flow rate amplitude is calculated; wherein, the respiratory flow rate amplitude is equal to the product of the average respiratory flow rate value and a preset coefficient threshold. Based on a sliding window of sampling point time, the index position of the respiratory flow rate amplitude in the respiratory airflow waveform data of the current respiratory cycle is determined, and the first reference point is formed according to the index position and the respiratory flow rate amplitude.

7. The inhalation triggering control system according to claim 5, characterized in that, The phrase "analyzing the signal characteristics of the respiratory airflow velocity waveform data to determine the second reference point within the current respiratory cycle" specifically includes: Set an end-expiratory baseline; wherein, the respiratory airflow velocity corresponding to the end-expiratory baseline is 0. Based on a sliding window of sampling point time, the first intersection point of the end-expiratory baseline and the respiratory airflow velocity waveform data is determined to form the second reference point; wherein, the horizontal coordinate of the second reference point is the index value corresponding to the first intersection point position, and the vertical coordinate is 0.

8. The inhalation triggering control system according to claim 1, characterized in that, The phrase "determining the set of respiratory velocity sampling points corresponding to the respiratory airflow velocity waveform data based on the end-expiratory dynamic straight line" specifically includes: Set and determine the position of the first intersection point between the end-expiratory baseline and the respiratory airflow velocity waveform data; Using a preset number of sampling points, after obtaining the position of the first intersection point, several sampling points corresponding to the respiratory airflow velocity waveform data where the respiratory airflow velocity is greater than 0 are formed to create the respiratory flow velocity sampling point set.

9. The inhalation triggering control system according to claim 1, characterized in that, The step of "calculating the distance between each respiratory flow sampling point and the end-expiratory dynamic straight line, and determining the corresponding inspiratory trigger point based on the distance value" specifically includes: Calculate the distance between each respiratory flow sampling point and the end-expiratory dynamic straight line, and take the respiratory flow sampling point corresponding to the maximum distance value as the undetermined inspiratory trigger point; The system sets and determines whether the pending inspiratory trigger point is the inspiratory trigger point based on the number of intersections between the end-expiratory baseline and the respiratory airflow velocity waveform data.

10. The inhalation triggering control system according to claim 1, characterized in that, The step of "calculating the distance between each respiratory flow sampling point and the end-expiratory dynamic straight line, and determining the corresponding inspiratory trigger point based on the distance value" specifically includes: Calculate the area of ​​several corresponding triangles based on the distance between each respiratory flow sampling point and the end-expiratory dynamic straight line, and take the respiratory flow sampling point corresponding to the largest triangle area as the undetermined inspiratory trigger point. The system sets and determines whether the pending inspiratory trigger point is the inspiratory trigger point based on the number of intersections between the end-expiratory baseline and the respiratory airflow velocity waveform data.

11. The inhalation triggering control system according to claim 9, characterized in that, The phrase "setting and determining whether the pending inspiratory trigger point is the inspiratory trigger point based on the number of intersections between the end-expiratory baseline and the respiratory airflow velocity waveform data" specifically includes: Determine whether the number of intersections between the end-expiratory baseline and the respiratory airflow velocity waveform data is greater than 1; If so, determine whether the distance values ​​of several respiratory flow sampling points after the undetermined inspiratory trigger point are monotonically decreasing; If so, then the pending inspiratory trigger point is determined as the inspiratory trigger point of the current respiratory cycle.

12. The inhalation triggering control system according to claim 9, characterized in that, The phrase "setting and determining whether the pending inspiratory trigger point is the inspiratory trigger point based on the number of intersections between the end-expiratory baseline and the respiratory airflow velocity waveform data" specifically includes: Determine whether the number of intersections between the end-expiratory baseline and the respiratory airflow velocity waveform data is equal to 1; If so, determine whether the distance values ​​of several respiratory flow sampling points after the undetermined inspiratory trigger point are monotonically increasing; If so, determine whether the respiratory airflow velocity corresponding to the undetermined inhalation trigger point is greater than or equal to a preset airflow velocity threshold. If the respiratory airflow velocity corresponding to the pending inspiratory trigger point is greater than or equal to the preset airflow velocity threshold, then the pending inspiratory trigger point is determined to be the inspiratory trigger point of the current respiratory cycle. If the respiratory airflow velocity corresponding to the pending inspiratory trigger point is less than the preset airflow velocity threshold, the ventilator will not trigger the inspiratory mode during the current respiratory cycle.

13. The inhalation triggering control system according to claim 1, characterized in that, After "determining the corresponding inhalation trigger point based on the distance value", the method further includes: The inspiratory trigger sensitivity curve was obtained by fitting several inspiratory trigger points and several gas leakage rates within several respiratory cycles. Based on the inspiratory trigger sensitivity curve, the inspiratory trigger point of the current respiratory cycle is dynamically adjusted; The inspiratory trigger sensitivity curve is a quadratic curve with the gas leakage rate at the ventilator mask end as the independent variable and the inspiratory trigger sensitivity as the dependent variable.

14. An inhalation trigger control system, characterized in that, include: The data acquisition unit is used to collect respiratory gas flow rate data and airway pressure data within a unit respiratory cycle. The data preprocessing unit is used to filter the collected respiratory gas flow data and airway pressure data to obtain effective respiratory gas flow data and effective airway pressure data. The breathing pattern signal extraction unit is used to calculate the gas leakage rate and breathing airflow rate waveform data at the ventilator mask end based on the effective breathing gas flow rate data and the effective airway pressure data. The inspiratory trigger detection unit is used to analyze and extract the signal features of the respiratory airflow velocity waveform data and construct the end-expiratory dynamic straight line; it is used to determine the set of respiratory flow velocity sampling points corresponding to the respiratory airflow velocity waveform data based on the end-expiratory dynamic straight line. The distance between each respiratory flow sampling point and the end-expiratory dynamic line is calculated, and the corresponding inspiratory trigger point is determined based on the distance value. The end-expiratory dynamic line represents the change in respiratory airflow velocity at the end of the expiratory phase within a unit respiratory cycle.

15. A ventilator, characterized in that, include: A memory and a processor, the memory having a computer program executable on the processor, the processor executing the program to implement the steps of the method performed by the inhalation trigger control system as described in any one of claims 1-13.

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