Detection method for inspiration triggering, respiratory support equipment and product

Abstract

The inspiration triggering detection method is applied to respiratory support equipment and comprises the steps that flow data and pressure data detected by the respiratory support equipment in real time are obtained; respectively calculating a flow change rate corresponding to the flow data and a pressure change rate corresponding to the pressure data; calculating a flow dynamic threshold according to the plurality of flow change rates in the historical data window; according to the multiple pressure change rates in the historical data window, a pressure dynamic threshold value is obtained through calculation; when the flow change rate is larger than the flow dynamic threshold value and the pressure change rate is smaller than the pressure dynamic threshold value, it is determined that the inspiration action is triggered; after it is determined that the inspiration action is triggered, inspiration support is provided for the patient. According to the method and the device, whether the inspiration action is triggered or not is jointly judged through the comparison result of the flow change rate corresponding to the flow data and the flow dynamic threshold value and the comparison result of the pressure change rate corresponding to the pressure data and the pressure dynamic threshold value, so that the accuracy of inspiration triggering judgment is improved.

Description

Technical Field

[0001] The present invention relates to the field of medical equipment, and in particular to an inhalation-triggered detection method, respiratory support equipment, and products. Background Art

[0002] At present, the inhalation trigger detection of ventilators / anesthesia machines is mainly achieved separately through the following methods. Flow triggering: monitoring the flow changes caused by the patient's inhalation, and determining it as an inhalation trigger when the flow exceeds a fixed value. Pressure triggering: monitoring the decrease in the patient's airway pressure, and determining it as an inhalation trigger when the airway pressure is lower than a fixed value. The above determination method has a high risk of misjudgment / missed judgment. This is because when the leakage of the respiratory system suddenly changes (such as the tube falling off, the mask leaking) or the patient's spontaneous breathing is unstable, the flow and pressure signals are easily interfered with, which will cause the fixed threshold method to fail; moreover, the above determination method mainly relies on empirical thresholds and cannot respond to changes in the patient's respiratory mechanics (such as airway resistance and compliance changes) in real time.

[0003] Therefore, how to improve the accuracy of inhalation trigger determination is a technical problem that needs to be solved urgently. Summary of the Invention

[0004] The main technical problem solved by the present invention is how to improve the accuracy of inhalation trigger determination.

[0005] According to a first aspect, an embodiment provides a method for detecting an inhalation trigger, which is applied to a respiratory support device, the method comprising:

[0006] Obtain real-time flow and pressure data from respiratory support equipment;

[0007] respectively calculating a flow rate change rate corresponding to the flow data and a pressure change rate corresponding to the pressure data;

[0008] The dynamic flow threshold is calculated based on multiple flow change rates within the historical data window;

[0009] Calculating a pressure dynamic threshold value based on multiple pressure change rates within the historical data window;

[0010] When the flow rate change rate is greater than the flow rate dynamic threshold and the pressure change rate is less than the pressure dynamic threshold, determining that an inhalation action is triggered;

[0011] After determining that the inhalation action is triggered, providing inhalation support to the patient.

[0012] According to a second aspect, an embodiment provides a respiratory support device, the respiratory support device comprising:

[0013] A ventilation module is used to connect to the patient through a ventilation tube to provide respiratory support for the patient;

[0014] a detection system, configured to detect when the ventilation module provides respiratory support to the patient and obtain flow data and pressure data;

[0015] Human-computer interaction device;

[0016] Controller for:

[0017] respectively calculating a flow rate change rate corresponding to the flow data and a pressure change rate corresponding to the pressure data;

[0018] The dynamic flow threshold is calculated based on multiple flow change rates within the historical data window;

[0019] Calculating a pressure dynamic threshold value based on multiple pressure change rates within the historical data window;

[0020] When the flow rate change rate is greater than the flow rate dynamic threshold and the pressure change rate is less than the pressure dynamic threshold, determining that an inhalation action is triggered;

[0021] After determining that the inhalation action is triggered, controlling the ventilation module to provide inhalation support for the patient.

[0022] According to the above-mentioned embodiment, a method for detecting an inhalation trigger is used to jointly determine whether an inhalation action has been triggered by comparing the flow rate change rate corresponding to the flow data with the flow dynamic threshold, and by comparing the pressure rate change rate corresponding to the pressure data with the pressure dynamic threshold, thereby improving the accuracy of the inhalation trigger determination. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Figure 1 A schematic flow chart of an inhalation-triggered detection method provided in this embodiment;

[0024] Figure 2 This is a structural block diagram of a respiratory support device provided in this embodiment. DETAILED DESCRIPTION

[0025] The present invention will be further described in detail below by means of specific embodiments in conjunction with the accompanying drawings. Similar elements in different embodiments are numbered with associated similar elements. In the following embodiments, many detailed descriptions are provided to enable the present application to be better understood. However, those skilled in the art will readily appreciate that some of the features may be omitted in different circumstances, or may be replaced by other elements, materials, or methods. In some cases, some operations related to the present application are not shown or described in the specification. This is to avoid the core portion of the present application being overwhelmed by excessive descriptions, and for those skilled in the art, it is not necessary to describe these related operations in detail. They will fully understand the related operations based on the description in the specification and the general technical knowledge in the art.

[0026] In addition, the features, operations, or characteristics described in the specification may be combined in any appropriate manner to form various embodiments. Furthermore, the steps or actions in the method description may be reordered or adjusted in a manner readily apparent to those skilled in the art. Therefore, the various sequences in the specification and drawings are provided solely for the purpose of clearly describing a particular embodiment and are not intended to be mandatory, unless otherwise specified.

[0027] The serial numbers assigned to components herein, such as "first," "second," etc., are used solely to distinguish the objects being described and do not convey any sequential or technical meaning. References to "connection" and "coupling" herein, unless otherwise specified, include both direct and indirect connections (couplings).

[0028] At present, some high-end ventilators or anesthesia machines and other equipment require different matching quantities when measuring the patient's inhalation or expiratory flow due to different usage scenarios. The inhalation trigger detection of traditional ventilators / anesthesia machines is mainly implemented separately through the following methods. Flow triggering: Monitor the flow changes caused by the patient's inhalation, and determine it as an inhalation trigger when the flow exceeds a fixed value. Pressure triggering: Monitor the decrease in the patient's airway pressure, and determine it as an inhalation trigger when the airway pressure is lower than a fixed value. Mixed triggering: Combines flow and airway pressure for comprehensive judgment. For example, when the flow exceeds a fixed value and the airway pressure is lower than a fixed value, it is determined to be an inhalation trigger. The above-mentioned determination method has a high risk of misjudgment / missed judgment. This is because when the leakage of the respiratory system suddenly changes (such as tubing detachment, mask leakage) or the patient's spontaneous breathing is unstable, the flow and pressure signals are easily disturbed, which will cause the fixed threshold method to fail. Moreover, the above-mentioned determination method mainly relies on empirical thresholds and cannot respond to changes in the patient's respiratory mechanics (such as airway resistance and compliance changes) in real time. In addition, the judgment of a single parameter (such as flow or airway pressure) requires the accumulation of more signal changes, which may cause trigger delays and affect human-machine synchronization.

[0029] In order to solve the above technical problems, the present application proposes a method for detecting inhalation triggering, which jointly determines whether the inhalation action is triggered by comparing the flow change rate corresponding to the real-time detected flow data and the flow dynamic threshold, and comparing the pressure change rate corresponding to the real-time detected pressure data and the pressure dynamic threshold. In this way, the accuracy of the inhalation trigger determination is improved through double judgment.

[0030] Please refer to Figure 1 , Figure 1 This is a flow chart of a method for detecting inhalation triggering provided in this embodiment. The detection method is applied to respiratory support equipment and specifically includes the following steps S101-S106:

[0031] Step S101: Acquire flow data and pressure data detected in real time by a respiratory support device.

[0032] It should be noted that respiratory support equipment refers to equipment used to help patients with respiratory distress maintain normal breathing. For example, the respiratory support equipment may be a miniaturized, portable ventilator or anesthesia machine. Alternatively, it may be a miniaturized, portable home ventilator or anesthesia machine. This application does not impose any limitations on this.

[0033] It should be noted that the flow data may be gas flow data of the patient during breathing detected by the respiratory support device, including gas flow data of the patient during inspiration or gas flow data of the patient during expiration. This application does not impose any limitation on this.

[0034] It should be noted that the pressure data may be the airway pressure of the patient during breathing as detected by the respiratory support device; for example, the pressure in the patient's airway during inhalation or during exhalation. This application does not impose any limitation on this.

[0035] In practical applications, after obtaining the flow data Q(t) and pressure data P(t) detected in real time by the respiratory support equipment, the flow data and pressure data can be preprocessed, such as filtering and denoising, to reduce environmental noise, electromagnetic interference, thermal noise of the respiratory support equipment itself, etc.

[0036] Step S102: Calculate the flow rate change rate corresponding to the flow data and the pressure change rate corresponding to the pressure data respectively.

[0037] It should be noted that the flow rate change rate represents the speed or magnitude of change of flow data over time. Similarly, the pressure change rate represents the speed or magnitude of change of pressure data over time.

[0038] In practical applications, the flow rate change rate can be obtained by time differentiation of the flow data Q(t) The pressure change rate can be obtained by time-differentiating the pressure data P(t) This application does not impose any limitation on the method of obtaining the flow rate change rate and the pressure change rate.

[0039] Step S103: Calculate a flow dynamic threshold value based on multiple flow change rates within the historical data window.

[0040] It should be noted that the historical data window represents a collection of historical data within a specific time period during data analysis or processing. This specific time period can be a period before the current moment and lasting a preset time period n (n>0). Specifically, it can be the period from a time prior to the current moment by a preset time period n to the current moment.

[0041] It should be noted that the flow rate change rate is used to characterize the speed of change of flow data.

[0042] In some embodiments, the dynamic flow threshold is calculated based on multiple flow change rates within a historical data window, including:

[0043] The mean and dispersion characterization of the multiple flow rate change rates within the historical data window are calculated based on the multiple flow rate change rates within the historical data window;

[0044] Obtain sensitivity coefficient and leakage compensation factor;

[0045] The dynamic flow threshold is calculated based on the mean value, the discreteness characterization quantity, the sensitivity coefficient, and the leakage compensation factor. Specifically, the dynamic flow threshold T_Q(t) is calculated according to the following formula:

[0046] T_Q(t)=μ_Q[tk,t]+β*σ_Q[tk,t]*ɑ(t)

[0047] Where [tk, t] represents the historical data window; k represents the duration of the historical data window (usually 3-5 breathing cycles); t represents time; β represents the sensitivity coefficient; α(t) represents the leakage compensation factor; μ_Q represents the mean of the flow rate change rate within the historical data window; σ_Q represents the discrete degree of the flow rate change rate within the historical data window.

[0048] It should be noted that the mean, discrete degree characterization, sensitivity coefficient, and leakage compensation factor in the flow dynamic threshold calculation formula can be expressed by the first mean, first discrete degree characterization, first sensitivity coefficient, and first leakage compensation factor.

[0049] It should be noted that the first mean of the multiple flow rate change rates within the historical data window represents the average of the multiple flow rate change rates within the time period corresponding to the historical window. In practical applications, this average value can be used as a representative value for the middle position or a specific position of the window. As the window gradually moves in the time series, a series of moving means can be calculated. Introducing this moving mean can reduce the impact of abnormal conditions (such as coughing, sighing, and swallowing).

[0050] It should be noted that the first discrete degree characterization quantity of the multiple flow rate change rates within the historical data window is used to characterize the degree to which the multiple flow rate change rates deviate from their average value. For example, the first discrete degree characterization quantity can be the standard deviation of the multiple flow rate change rates within the historical data window. This application does not impose any restrictions on this. In actual applications, the larger the first discrete degree characterization quantity, the more unstable the flow data detected by the respiratory support device; conversely, it is relatively stable.

[0051] It should be noted that the first sensitivity coefficient is used to measure the respiratory system's ability to respond to changes in input data or external conditions. Specifically, the first sensitivity coefficient is used to adjust the sensitivity of the flow dynamic threshold to abnormal values. In actual use, a higher first sensitivity coefficient helps to respond to sudden changes faster, but it may also lead to more false alarms. Therefore, the first sensitivity coefficient needs to be set according to the actual airway structure. The default first sensitivity coefficient is generally 1.5.

[0052] In some embodiments, obtaining the leakage compensation factor includes:

[0053] Obtain end-expiratory flow baseline offset and peak expiratory flow rate;

[0054] The leakage compensation factor is calculated based on the end-expiratory flow baseline offset and the peak expiratory flow rate.

[0055] In some embodiments, the leakage compensation factor is calculated based on the end-expiratory flow baseline offset and the peak expiratory flow rate, including:

[0056] ɑ(t)=1.2-0.5*(ΔQ_baseline / Q_peak)

[0057] Where ΔQ_baseline represents the end-expiratory flow baseline offset; Q_peak represents the peak expiratory flow rate.

[0058] It's important to note that the end-expiratory flow baseline offset represents the degree to which the end-expiratory flow curve deviates from the baseline. In practice, respiratory support equipment monitors the patient's end-expiratory flow in real time. The difference between the current end-expiratory flow and the baseline flow is calculated, resulting in ΔQ_baseline.

[0059] It should be noted that the peak expiratory flow rate represents the instantaneous flow rate when the expiratory flow rate is the fastest. In practical applications, Q_peak is the maximum expiratory flow rate during the expiratory period of a complete respiratory cycle.

[0060] In practical applications, the flow dynamic threshold can be adaptively calculated based on the mean and discrete degree characterization of multiple flow change rates of historical data (such as the latest 3 to 5 respiratory cycles).

[0061] The purpose of introducing the first leakage compensation factor into the calculation formula of the flow dynamic threshold is to reduce the sensitivity of the flow dynamic threshold when the respiratory system detects a sudden change in gas leakage. Specifically, when the respiratory system detects that there is a gas leak in the pipeline of the respiratory support equipment, the flow dynamic threshold can be appropriately relaxed or tightened according to the first leakage compensation factor without manual intervention. On the one hand, it can ensure that the alarm will not be falsely triggered due to minor leaks or noise; on the other hand, it can also ensure that a timely response can be made in the event of a larger leak, thereby improving the accuracy and robustness of the detection. It should be noted that the first leakage compensation factor can be dynamically adjusted according to the real-time monitored end-expiratory flow baseline offset and expiratory peak flow to adapt to different respiratory conditions and leakage conditions.

[0062] In practice, the respiratory system monitors the end-expiratory flow baseline offset in real time. When it continuously exceeds a threshold (e.g., 1.5 L / min) for a certain duration (e.g., 250 ms), the respiratory system triggers the first leak compensation factor and dynamically adjusts it according to its calculation formula. It should be noted that this threshold varies depending on the patient's age.

[0063] Step S104: Calculate a pressure dynamic threshold value based on multiple pressure change rates within the historical data window.

[0064] It should be noted that the historical data window represents a collection of historical data within a specific time period during data analysis or processing. This specific time period can be a period before the current moment and lasting a preset time period n (n>0). Specifically, it can be the period from a time prior to the current moment by a preset time period n to the current moment.

[0065] It should be noted that the pressure change rate is used to characterize the speed at which pressure data changes.

[0066] In some embodiments, the pressure dynamic threshold is calculated based on multiple pressure change rates within a historical data window, including:

[0067] The mean and dispersion characterization of the multiple pressure change rates within the historical data window are calculated based on the multiple pressure change rates within the historical data window;

[0068] Obtain sensitivity coefficient and leakage compensation factor;

[0069] The pressure dynamic threshold is calculated based on the mean value, the discrete degree characterization quantity, the sensitivity coefficient and the leakage compensation factor. Specifically, the pressure dynamic threshold T_P(t) is calculated according to the following formula:

[0070] T_P(t)=μ_P[tk,t]+β*σ_P[tk,t]*α(t)

[0071] Where [tk, t] represents the historical data window; k represents the duration of the historical data window (usually 3-5 breathing cycles); t represents time; β represents the sensitivity coefficient; ɑ(t) represents the leakage compensation factor; μ_P represents the mean value of the pressure change rate within the historical data window; σ_P represents the discrete degree of the pressure change rate within the historical data window.

[0072] It should be noted that the mean, dispersion indicator, sensitivity coefficient, and leakage compensation factor in the pressure dynamic threshold calculation formula can be represented by a second mean, second dispersion indicator, second sensitivity coefficient, and second leakage compensation factor. In practical applications, the second sensitivity coefficient and the first sensitivity coefficient can be the same; the second leakage compensation factor and the first leakage compensation factor can also be the same.

[0073] It should be noted that the second mean of the multiple pressure change rates within the historical data window represents the average of the multiple pressure change rates within the time period corresponding to the historical window. In practical applications, this average value can be used as a representative value for the middle position or a specific position of the window. As the window gradually moves in the time series, a series of moving means can be calculated. Introducing this moving mean can reduce the impact of abnormal conditions (such as coughing, sighing, and swallowing).

[0074] It should be noted that the second discrete degree characterization quantity of the multiple pressure change rates within the historical data window is used to characterize the degree to which the multiple pressure change rates deviate from their average value. For example, the second discrete degree characterization quantity can be the standard deviation of the multiple pressure change rates within the historical data window. This application does not impose any restrictions on this. In actual applications, the larger the second discrete degree characterization quantity, the more unstable the pressure data detected by the respiratory support device; conversely, it is relatively stable.

[0075] It should be noted that the second sensitivity coefficient is used to measure the respiratory system's responsiveness to changes in input data or external conditions. Specifically, the second sensitivity coefficient is used to adjust the sensitivity of the dynamic pressure threshold to abnormal values. In actual use, a higher second sensitivity coefficient helps to respond to sudden changes more quickly, but it may also lead to more false alarms. Therefore, the second sensitivity coefficient needs to be set according to the actual airway structure. The default second sensitivity coefficient is generally 1.5.

[0076] In practical applications, the pressure dynamic threshold can be adaptively calculated based on the mean and discreteness representation of multiple pressure change rates of historical data (such as the latest 3 to 5 respiratory cycles).

[0077] The inclusion of a second leakage compensation factor in the dynamic pressure threshold calculation formula is intended to reduce the sensitivity of the dynamic pressure threshold when the respiratory system detects a sudden change in gas leakage. Specifically, when the respiratory system detects a gas leak in the respiratory support device's tubing, the dynamic pressure threshold can be appropriately relaxed or tightened based on this second leakage compensation factor to ensure that minor leaks do not falsely trigger alarms. The value of this second leakage compensation factor can be adaptively adjusted based on the specific leakage situation.

[0078] Step S105: When the flow rate change rate is greater than the flow rate dynamic threshold and the pressure change rate is less than the pressure dynamic threshold, it is determined that the inhalation action is triggered.

[0079] It should be noted that when the flow rate change rate is greater than the flow dynamic threshold and the pressure change rate is less than the pressure dynamic threshold, it means that the patient needs respiratory support equipment to provide inhalation support. In other words, the inhalation triggering action at this time is effective.

[0080] Step S106: After determining that the inhalation action is triggered, provide inhalation support for the patient.

[0081] In some embodiments, when the flow rate change rate is less than or equal to the flow rate dynamic threshold and the pressure change rate is greater than or equal to the pressure dynamic threshold, it is determined that the inhalation action is not triggered.

[0082] It should be noted that when the flow rate change rate is less than or equal to the flow dynamic threshold, and the pressure change rate is greater than or equal to the pressure dynamic threshold, the patient does not need respiratory support equipment to provide inspiratory support. In other words, even if an inspiratory action is triggered at this time, the respiratory system will determine that the inspiratory triggering action is invalid.

[0083] In some embodiments, when the flow change rate is greater than the flow dynamic threshold and the pressure change rate is greater than or equal to the pressure dynamic threshold, a flow speed parameter reflecting the speed of change of the flow change rate in the subsequent preset intermittent period is calculated based on the flow change rate in the subsequent preset intermittent period; when the flow change rate in the subsequent preset intermittent period is greater than the flow dynamic threshold and the flow speed parameter is greater than zero, it is determined that the inhalation action is triggered; otherwise, it is determined that the inhalation action is not triggered.

[0084] It should be noted that when the flow change rate is greater than the flow dynamic threshold and the pressure change rate is greater than or equal to the pressure dynamic threshold, the patient may need respiratory support equipment to provide inhalation support, or may not need respiratory support equipment to provide inhalation support. This requires further judgment.

[0085] For example, when the respiratory system detects the rate of change of flow The corresponding flow dynamic threshold is met, but the pressure change rate When the corresponding pressure dynamic threshold is not met, the respiratory system will start the delay waiting mechanism, and then the respiratory system will enter a short waiting period. During the waiting period, the respiratory system will continue to record the flow rate change rate. and flow rate parameters The flow data sequence during this period is analyzed through statistical methods, machine learning algorithms, or moving average techniques to determine whether there is an abnormal trend in the flow data sequence.

[0086] Specifically, during the entire delay period (tens of milliseconds), if Satisfy at the same time It can be determined that the flow data sequence does have an upward trend, which also shows that the phenomenon that the initial flow change rate does not meet the flow dynamic threshold is not an accidental fluctuation. At this time, it can be determined that the inhalation action has been triggered, and respiratory support equipment is needed to provide inhalation support for the patient. In this way, the delay time of inhalation triggering can be effectively shortened; if the flow data sequence has no obvious trend or the trend reverses back to the normal range, it means that the phenomenon that the initial flow change rate does not meet the flow dynamic threshold may be caused by transient factors. At this time, it can be determined that the inhalation action has not been triggered, so there is no need for respiratory support equipment to provide inhalation support for the patient.

[0087] In some embodiments, when the flow change rate is less than or equal to the flow dynamic threshold and the pressure change rate is less than the pressure dynamic threshold, a pressure velocity parameter reflecting the speed of change of the pressure change rate in the subsequent preset intermittent period is calculated based on the pressure change rate in the subsequent preset intermittent period; when the pressure change rate in the subsequent preset intermittent period is less than the pressure dynamic threshold and the pressure velocity parameter is less than zero, it is determined that the inhalation action is triggered; otherwise, it is determined that the inhalation action is not triggered.

[0088] It should be noted that when the flow change rate is less than or equal to the flow dynamic threshold, and the pressure change rate is less than the pressure dynamic threshold, the patient may need respiratory support equipment to provide inhalation support, or may not need respiratory support equipment to provide inhalation support. This requires further judgment.

[0089] For example, when the respiratory system detects the rate of pressure change The corresponding pressure dynamic threshold is met, but the flow rate change rate When the corresponding pressure dynamic threshold is not met, the respiratory system will start the delay waiting mechanism, and then the respiratory system will enter a short waiting period. During the waiting period, the respiratory system will continue to record the pressure change rate. And pressure-velocity parameters The pressure data series during this period is analyzed through statistical methods, machine learning algorithms, or moving average techniques to determine whether there is an abnormal trend in the pressure data series.

[0090] Specifically, during the entire delay period (tens of milliseconds), if Satisfy at the same time It can be determined that the pressure data sequence does have a downward trend, which also shows that the phenomenon that the initial pressure change rate does not meet the pressure dynamic threshold is not an accidental fluctuation. At this time, it can be determined that the inhalation action has been triggered, and respiratory support equipment is needed to provide inhalation support for the patient. In this way, the delay time of inhalation triggering can be effectively shortened; if the pressure data sequence has no obvious trend or the trend reverses back to the normal range, it means that the phenomenon that the initial pressure change rate does not meet the pressure dynamic threshold may be caused by transient factors (fluctuations in airway resistance or sudden changes in gas leakage). At this time, it can be determined that the inhalation action has not been triggered, so there is no need for respiratory support equipment to provide inhalation support for the patient.

[0091] In some embodiments, after determining that an inhalation action has been triggered, providing inhalation support to the patient includes:

[0092] Acquire weak inspiratory effort characteristic data from flow rate change and / or pressure rate change;

[0093] After determining that the inspiratory action is triggered, inspiratory support is provided to the patient based on the weak inspiratory effort characteristic data.

[0094] In practical applications, or The weak inspiratory effort characteristics (airway pressure change trend, airway flow change trend) are captured from the changing trend of the airway pressure, and inspiratory support is given to the patient based on the weak inspiratory effort characteristics, thereby improving human-machine coordination.

[0095] It should be noted that after determining that the inspiratory trigger is valid, the respiratory support device will provide corresponding inspiratory support to the patient according to the ventilation parameters (tidal volume, respiratory rate, peak airway pressure, and inspiratory pressure) set by the user (medical staff) to meet the patient's inspiratory needs. Before providing inspiratory support to the patient, the respiratory support device maintains the patient's positive end-expiratory pressure according to another ventilation parameter (positive end-expiratory pressure) set by the user (medical staff).

[0096] The present embodiment provides a method for detecting an inhalation trigger, which is applied to a respiratory support device, the method comprising: obtaining flow data and pressure data detected in real time by the respiratory support device; respectively calculating the flow change rate corresponding to the flow data and the pressure change rate corresponding to the pressure data; calculating a flow dynamic threshold value based on multiple flow change rates within a historical data window; calculating a pressure dynamic threshold value based on multiple pressure change rates within a historical data window; determining that an inhalation action is triggered when the flow change rate is greater than the flow dynamic threshold value and the pressure change rate is less than the pressure dynamic threshold value; and providing inhalation support to the patient after determining that the inhalation action is triggered. The present application jointly determines whether an inhalation action is triggered by comparing the flow change rate corresponding to the flow data with the flow dynamic threshold value, and by comparing the pressure change rate corresponding to the pressure data with the pressure dynamic threshold value. In this way, the accuracy of the inhalation trigger determination is improved through double determination.

[0097] Please refer to Figure 2 , Figure 2 This is a structural block diagram of a respiratory support device provided in this embodiment.

[0098] The respiratory support device 20 comprises:

[0099] The ventilation module 201 is used to connect to the patient through a ventilation circuit to provide respiratory support for the patient.

[0100] The detection system 202 is used to detect when the ventilation module provides respiratory support to the patient and obtain flow data and pressure data, that is, to perform the above step S101.

[0101] Human-computer interaction device 203.

[0102] The controller 204 is configured to:

[0103] The flow rate change rate corresponding to the flow data and the pressure rate change rate corresponding to the pressure data are calculated respectively; a flow dynamic threshold is calculated based on multiple flow rate change rates within the historical data window; a pressure dynamic threshold is calculated based on multiple pressure change rates within the historical data window; when the flow rate change rate is greater than the flow dynamic threshold and the pressure change rate is less than the pressure dynamic threshold, an inhalation action is determined to be triggered; after determining that an inhalation action is triggered, the ventilation module is controlled to provide inhalation support to the patient. This is to execute the aforementioned steps S102-S106. The specific functions of the controller 204 have been described in detail in steps S102-S106 and are not further described here.

[0104] The present embodiment provides a respiratory support device, comprising: a ventilation module, which is used to connect to a patient through a ventilation line to provide respiratory support for the patient. A detection system, which is used to perform detection when the ventilation module provides respiratory support for the patient, and obtain flow data and pressure data. A human-computer interaction device. A controller, which is used to: respectively calculate the flow change rate corresponding to the flow data and the pressure change rate corresponding to the pressure data; calculate the flow dynamic threshold value based on multiple flow change rates in the historical data window; calculate the pressure dynamic threshold value based on multiple pressure change rates in the historical data window; when the flow change rate is greater than the flow dynamic threshold value, and the pressure change rate is less than the pressure dynamic threshold value, determine that the inhalation action is triggered; after determining that the inhalation action is triggered, control the ventilation module to provide inhalation support for the patient. The present application jointly determines whether the inhalation action is triggered by comparing the flow change rate corresponding to the flow data and the flow dynamic threshold value, and comparing the pressure change rate corresponding to the pressure data and the pressure dynamic threshold value. In this way, the accuracy of the inhalation trigger determination is improved through double determination.

[0105] Those skilled in the art will appreciate that all or part of the functions of the various methods in the above embodiments can be implemented by hardware or by computer program. When all or part of the functions in the above embodiments are implemented by computer program, the program can be stored in a computer-readable storage medium, and the storage medium can include: read-only memory, random access memory, disk, optical disk, hard disk, etc., and the program is executed by a computer to implement the above functions. For example, the program is stored in the memory of the device, and when the program in the memory is executed by the processor, all or part of the above functions can be implemented. In addition, when all or part of the functions in the above embodiments are implemented by computer program, the program can also be stored in a storage medium such as a server, another computer, disk, optical disk, flash disk or mobile hard disk, and saved in the memory of the local device by downloading or copying, or the system of the local device is updated. When the program in the memory is executed by the processor, all or part of the functions in the above embodiments can be implemented.

[0106] The above examples are used to illustrate the present invention, which are only used to help understand the present invention and are not intended to limit the present invention. Those skilled in the art can make several simple deductions, modifications or substitutions based on the concept of the present invention.

Claims

1. A method for detecting an inhalation trigger, applied to a respiratory support device, characterized in that: The method comprises: Obtain real-time flow and pressure data from respiratory support equipment; respectively calculating a flow rate change rate corresponding to the flow data and a pressure change rate corresponding to the pressure data; The dynamic flow threshold is calculated based on multiple flow change rates within the historical data window; Calculating a pressure dynamic threshold value based on multiple pressure change rates within the historical data window; When the flow rate change rate is greater than the flow rate dynamic threshold and the pressure change rate is less than the pressure dynamic threshold, determining that an inhalation action is triggered; After determining that the inhalation action is triggered, providing inhalation support to the patient.

2. The method according to claim 1, wherein The flow dynamic threshold is calculated based on multiple flow change rates in the historical data window, including: Calculating the mean and dispersion characterization of the multiple flow rate change rates within the historical data window according to the multiple flow rate change rates within the historical data window; Obtain sensitivity coefficient and leakage compensation factor; A flow dynamic threshold is calculated based on the mean value, the discrete degree characterization quantity, the sensitivity coefficient and the leakage compensation factor.

3. The method according to claim 1, wherein The pressure dynamic threshold is calculated based on the multiple pressure change rates in the historical data window, including: Calculating the mean and dispersion characterization of the multiple pressure change rates within the historical data window according to the multiple pressure change rates within the historical data window; Obtain sensitivity coefficient and leakage compensation factor; A pressure dynamic threshold is calculated based on the mean value, the discrete degree characterization quantity, the sensitivity coefficient and the leakage compensation factor.

4. The method according to claim 2 or 3, wherein: The obtaining of the leakage compensation factor comprises: Obtain end-expiratory flow baseline offset and peak expiratory flow rate; The leakage compensation factor is calculated according to the end-expiratory flow baseline offset and the expiratory peak flow rate.

5. The method according to claim 1, wherein The method further comprises: When the flow rate change rate is less than or equal to the flow rate dynamic threshold, and the pressure change rate is greater than or equal to the pressure dynamic threshold, it is determined that the inhalation action is not triggered.

6. The method according to claim 1, wherein The method further comprises: When the flow rate change rate is greater than the flow dynamic threshold and the pressure change rate is greater than or equal to the pressure dynamic threshold, calculating a flow velocity parameter in the subsequent preset intermittent period for reflecting the change speed of the flow rate change rate according to the flow rate change rate in the subsequent preset intermittent period; When the flow rate change rate is greater than the flow dynamic threshold value and the flow rate speed parameter is greater than zero during the subsequent preset intermittent period, it is determined that the inhalation action is triggered; otherwise, it is determined that the inhalation action is not triggered.

7. The method according to claim 1, wherein The method further comprises: When the flow rate change rate is less than or equal to the flow rate dynamic threshold, and the pressure change rate is less than the pressure dynamic threshold, calculating a pressure velocity parameter in the subsequent preset intermittent period, which is used to reflect the speed of change of the pressure change rate, according to the pressure change rate in the subsequent preset intermittent period; When the pressure change rate is less than the pressure dynamic threshold value and the pressure speed parameter is less than zero during the subsequent preset intermittent period, it is determined that the inhalation action is triggered; otherwise, it is determined that the inhalation action is not triggered.

8. The method according to claim 1, wherein After determining that the inhalation action is triggered, providing inhalation support to the patient includes: acquiring weak inspiratory effort characteristic data from the flow rate change rate and / or the pressure change rate; After determining that the inhalation action is triggered, providing inhalation support for the patient according to the weak inhalation effort characteristic data.

9. A respiratory support device, characterized in that The respiratory support device comprises: A ventilation module is used to connect to the patient through a ventilation tube to provide respiratory support for the patient; a detection system, configured to detect when the ventilation module provides respiratory support to the patient and obtain flow data and pressure data; Human-computer interaction device; Controller for: respectively calculating a flow rate change rate corresponding to the flow data and a pressure change rate corresponding to the pressure data; The dynamic flow threshold is calculated based on multiple flow change rates within the historical data window; Calculating a pressure dynamic threshold value based on multiple pressure change rates within the historical data window; When the flow rate change rate is greater than the flow rate dynamic threshold and the pressure change rate is less than the pressure dynamic threshold, determining that an inhalation action is triggered; After determining that the inhalation action is triggered, controlling the ventilation module to provide inhalation support for the patient.

10. A computer program product comprising a computer program and / or instructions, characterized in that When the computer program and / or instructions are executed by a processor, the method according to any one of claims 1 to 8 is implemented.

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