A PAV parameter adjustment method and device for a ventilator

Abstract

This application provides a method and apparatus for adjusting PAV parameters of a ventilator. The method determines multiple sets of pre-ventilation characteristic parameters and their corresponding initial proportional assist ventilation (PAV) parameter sets based on a predetermined sinusoidal flow ventilation waveform and a preset output time of the waveform. When PAV ventilation is performed using the initial PAV parameter set, ventilation detection information from a flow and sensor module is acquired. This ventilation detection information is the detection information when the ventilator is in PAV mode. The detection information includes at least one or more of the following: flow rate and pressure. Based on the ventilation detection information and preset assisted ventilation information, a preset parameter update strategy is matched to update the initial PAV parameter set according to the strategy. Based on the updated PAV parameter set, a PAV control command is generated to control the corresponding pressure value of the ventilator's PAV mode in real time according to the updated PAV parameter set.

Description

Technical Field

[0001] This application relates to the field of medical device technology, and in particular to a method and apparatus for adjusting the parameters of proportional assist ventilation (PAV) for a ventilator. Background Technology

[0002] A ventilator is a medical device used to rescue and treat acute or chronic respiratory diseases. The main function of a ventilator is its ventilation mode. The ventilation mode describes the changes in pressure, flow rate, and volume over time during ventilator ventilation, as well as the logic of the transition between inspiratory and expiratory phases. Among the spontaneous ventilation modes of a ventilator are proportional ventilation (PAV) and pressure support ventilation (PSV).

[0003] Currently, the implementation of PAV mode largely requires knowledge of respiratory mechanics parameters such as airway resistance and lung elasticity. Furthermore, users need to set (titrate) the assist factor before proportional ventilation can be performed in PAV mode. Firstly, the accuracy of obtaining respiratory mechanics parameters during actual ventilator use is not high. Secondly, setting the assist factor relies too heavily on user experience; setting it too high or too low will negatively impact the patient's experience, thus making PAV mode unsuitable for practical use. Summary of the Invention

[0004] This application provides a method and apparatus for adjusting PAV parameters of a ventilator, which addresses the problem that current ventilators in PAV mode are not conducive to normal use by users and affect the patient's experience.

[0005] On one hand, embodiments of this application provide a method for adjusting PAV parameters of a ventilator, the method comprising:

[0006] Based on a predetermined sinusoidal flow ventilation waveform, determine multiple pre-ventilation characteristic parameter sets and their corresponding initial proportional auxiliary ventilation (PAV) parameter sets corresponding to a predetermined output time of the sinusoidal flow ventilation waveform.

[0007] When PAV ventilation is performed using the initial PAV parameter set, ventilation detection information is acquired from the flow and sensing module; wherein, the ventilation detection information is the detection information when the ventilator is ventilated in PAV mode; the detection information includes at least one or more of the following: flow rate, pressure;

[0008] Based on the ventilation detection information and the preset assisted ventilation information, a preset parameter update strategy is matched to update the initial PAV parameter set according to the parameter update strategy.

[0009] Based on the updated PAV parameter set, PAV control commands are generated to control the corresponding pressure value of the ventilator's PAV mode in real time according to the updated PAV parameter set.

[0010] In one implementation of this application, a pre-ventilation trigger signal is generated to cause the ventilator to supply pressurized gas with the sinusoidal flow ventilation waveform within a preset output time; the preset output time includes at least the time for the patient to receive oxygen at a preset number of breaths.

[0011] The flow rate and sensing module determines the pre-ventilation detection information for each breath within the preset output time; the pre-ventilation detection information includes at least: flow rate, pressure, breathing start time, and breathing end time;

[0012] The pre-ventilation detection information is analyzed, and the pre-ventilation characteristic parameter set corresponding to each breath is determined;

[0013] Based on the preset initial PAV parameters, a model is determined, and a set of undetermined PAV parameters corresponding to each of the pre-ventilation characteristic parameter groups is determined; the set of undetermined PAV parameters includes at least capacity auxiliary parameters and flow auxiliary parameters.

[0014] Based on each of the undetermined PAV parameter sets, the initial PAV parameter set is determined.

[0015] In one implementation of this application, the inspiratory pressure data in the pre-ventilation detection information is determined, and the peak inspiratory pressure and the terminal inspiratory pressure value in the inspiratory pressure data are determined; and

[0016] Determine the positive end-expiratory pressure and tidal volume in the pre-ventilation detection information;

[0017] Based on the preset initial PAV parameters, the model is determined, and the set of undetermined PAV parameters corresponding to each of the pre-ventilation characteristic parameter groups is determined, specifically including:

[0018] The volume auxiliary parameter is determined based on the terminal inspiratory pressure, the positive end-expiratory pressure, and the tidal volume.

[0019] The flow assist parameter is determined based on the peak inspiratory pressure, the volume assist parameter, the positive end-expiratory pressure, and the flow rate and volume data at the time corresponding to the peak inspiratory pressure.

[0020] In one implementation of this application, taking the breathing start time as the starting point and the breathing end time as the ending point, the flow rate of the pre-ventilation detection information corresponding to one breath is integrated to determine the maximum and minimum inspiratory volume values ​​of one breath.

[0021] The initial tidal volume corresponding to one breath is determined based on the maximum inspiratory volume value, the minimum inspiratory volume value, and the first preset formula.

[0022] Calculate the moving average of the initial tidal volume corresponding to each breath in the pre-ventilation detection information, and use the moving average as the tidal volume in the pre-ventilation detection information.

[0023] In one implementation of this application, the ventilation detection information is determined by the number of consecutive breaths in the history of a predetermined number of breaths and the reciprocal of the difference between the end time and the start time of each breath; the number of consecutive breaths in the history of a predetermined number of breaths is the number of breaths prior to the current breath.

[0024] Calculate the product of the reciprocal of each difference and a predetermined unit of time, and use each product as the single respiratory rate of each breath; and use the moving average of each single respiratory rate as the respiratory rate of the current breath.

[0025] Based on the flow rate of the ventilation detection information, the tidal volume of the current breath is determined;

[0026] Based on the matching results of the respiratory rate value, the tidal volume, and the assisted ventilation information, a corresponding parameter update strategy is determined; wherein, the assisted ventilation information includes a preset target respiratory rate value and a target tidal volume.

[0027] In one implementation of this application, a Cartesian coordinate system is established with respiratory rate as the horizontal axis and respiratory volume as the vertical axis;

[0028] Based on the target respiratory rate, target tidal volume, and preset multiple level interval division parameters of the assisted ventilation information, multiple level interval division neighborhoods are generated, composed of different level interval division parameters, target respiratory rate, and target tidal volume.

[0029] Based on the neighborhood division of each level interval, a level interval division region is generated in the Cartesian coordinate system.

[0030] The coordinate matching level intervals corresponding to the respiratory rate value and the tidal volume are determined, and a preset parameter update strategy is determined based on the matching level intervals; the parameter update strategy includes the parameter adjustment amplitude and parameter adjustment direction in the PAV parameter set.

[0031] In one implementation of this application, the updated PAV parameter set is used as the initial PAV parameter set, and PAV ventilation is performed using the updated initial PAV parameter set to obtain the corresponding ventilation detection information.

[0032] Based on the matching results of the ventilation detection information and the assisted ventilation information corresponding to each breath, determine whether the parameters in the initial PAV parameter set are parameters to be updated;

[0033] If so, before each breath begins, update the parameters in the initial PAV parameter set until the matching result of the respiratory rate value, tidal volume and assisted ventilation information corresponding to the ventilation detection information meets the preset conditions; the preset conditions are that the absolute values ​​of the differences between the respiratory rate value and the target respiratory rate value and the tidal volume and the target tidal volume are less than the preset values.

[0034] In one implementation of this application, after generating the PAV control command, the undetermined pressure value and the undetermined pressure change curve output by the PAV parameter set are determined according to the second preset formula.

[0035] Based on the slope value of the undetermined pressure change curve, the extreme pressure value corresponding to the extreme point of the undetermined pressure change curve, and the corresponding limit, the undetermined pressure values ​​in the undetermined pressure change curve are limited and adjusted so that the limited and adjusted undetermined pressure values ​​are input into the pressure controller of the ventilator to control the corresponding pressure value of the ventilator's PAV mode in real time; the limit includes a slope value limit and a maximum value limit; the limit is used to adjust the value of each undetermined pressure value.

[0036] In one implementation of this application, after updating the PAV parameter set, the PAV parameter sets corresponding to a preset number of breaths and the parameter update direction of each PAV parameter set are determined; the parameter update direction includes a positive update direction and a negative update direction.

[0037] Based on the parameter update direction and the change in parameter distance between each parameter in the PAV parameter set and the corresponding parameter in the assisted ventilation information, the parameter update direction of the current breathing is updated, and the PAV parameter set is updated.

[0038] On the other hand, embodiments of this application also provide a PAV parameter adjustment device for a ventilator, the device comprising:

[0039] The determination module is used to determine, based on a predetermined sinusoidal flow ventilation waveform, multiple pre-ventilation characteristic parameter sets corresponding to a preset output time of the sinusoidal flow ventilation waveform and their corresponding initial proportional auxiliary ventilation (PAV) parameter sets.

[0040] The acquisition module is used to acquire ventilation detection information from the flow and sensing module when PAV ventilation is performed with the initial PAV parameter set; wherein the ventilation detection information is the detection information when the ventilator is ventilated in PAV mode; the detection information includes at least one or more of the following: flow rate and pressure;

[0041] The matching module is used to match a preset parameter update strategy based on the ventilation detection information and the preset auxiliary ventilation information, so as to update the initial PAV parameter set according to the parameter update strategy.

[0042] The generation module is used to generate PAV control commands based on the updated PAV parameter set, so as to control the corresponding pressure value of the PAV mode of the ventilator in real time according to the updated PAV parameter set.

[0043] By outputting a mixed gas with a predetermined sinusoidal flow rate ventilation waveform within a preset output time, the initial PAV parameter set is determined. PAV ventilation is then performed, and the initial PAV parameter set is updated based on the previous breath to control the pressure value corresponding to the ventilator's PAV mode. By determining the initial PAV parameters through the aforementioned volume-controlled sinusoidal ventilation, the auxiliary parameters of the PAV mode are initially in a relatively ideal state, ensuring patient comfort with each subsequent breath. This application allows users to use the PAV mode normally without needing to know complex respiratory mechanics parameters such as airway resistance and lung elasticity, nor to titrate the initial auxiliary coefficient. Furthermore, this application's mechanical ventilation model, which integrates negative and positive feedback mechanisms, is more user-friendly, safer, and more comfortable.

[0044] This application utilizes a feedback regulation mechanism based on tidal volume and respiratory rate, overcoming the shortcomings of existing proportional pressure assist (PAV) modes where users lack a basis for setting mode assist parameters. Furthermore, this application provides a multi-level automatic adjustment update strategy for assist parameters, ensuring patient freedom of breathing while balancing safety and comfort. This allows patients to autonomously control the size and rhythm of each breath, improving the user experience. Attached Figure Description

[0045] The accompanying drawings, which are included to provide a further understanding of this application and form part of this application, illustrate exemplary embodiments and are used to explain this application, but do not constitute an undue limitation of this application. In the drawings:

[0046] Figure 1 This is a schematic diagram of respiratory parameter waveforms in a PAV parameter adjustment method for a ventilator according to an embodiment of this application;

[0047] Figure 2This is a schematic diagram of a ventilator corresponding to a PAV parameter adjustment method for a ventilator in an embodiment of this application;

[0048] Figure 3 This is a schematic diagram of the dual-limb airway structure of a ventilator corresponding to a PAV parameter adjustment method for a ventilator in an embodiment of this application;

[0049] Figure 4 This is a schematic flowchart of a PAV parameter adjustment method for a ventilator in an embodiment of this application;

[0050] Figure 5 This is a schematic diagram of the pre-ventilation characteristic parameters in a PAV parameter adjustment method for a ventilator according to an embodiment of this application.

[0051] Figure 6 This is a schematic diagram of the grade interval division region in a PAV parameter adjustment method for a ventilator according to an embodiment of this application;

[0052] Figure 7 This is a schematic diagram of a PAV ventilation process in a PAV parameter adjustment method for a ventilator according to an embodiment of this application.

[0053] Figure 8 This is a schematic diagram of another process for adjusting PAV parameters of a ventilator in an embodiment of this application;

[0054] Figure 9 This is a schematic diagram of a PAV parameter adjustment device for a ventilator in an embodiment of this application. Detailed Implementation

[0055] To make the objectives, technical solutions, and advantages of this application clearer, the technical solutions of this application will be clearly and completely described below in conjunction with specific embodiments and corresponding drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of them. Based on the embodiments in this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0056] A ventilator is a medical device used to rescue and treat acute or chronic respiratory diseases. The main function of a ventilator is its ventilation mode. A ventilation mode describes the changes in pressure, flow rate, and volume over time during ventilator ventilation, as well as the logic of the transition between the inspiratory and expiratory phases. Since the invention of the ventilator, many ventilation modes have emerged. There are various classification methods for ventilation modes. Based on the intensity of the patient's voluntary participation, they can be divided into three categories: mandatory ventilation (CV), assisted ventilation (AV), and spontaneous ventilation (S). Spontaneous ventilation modes can be further divided into two types: pressure support ventilation (PSV) and proportional pressure-assisted ventilation (PAV). PSV is a standard mode found in all commercially available ventilators. Its pressure target for the inspiratory phase is a constant setpoint (except for a small pressure ramp at the beginning of inspiration), i.e., Ptarget(t) = P_set. From a control principle perspective, it is a pressure negative feedback control mode. Unlike PSV, PAV is a positive feedback control mode (positive amplification of spontaneous breathing effort). In PAV mode, the inspiratory pressure target is time-varying, proportional to both flow rate and volume: Ptarget(t) = KF × F(t) + KV × V(t). The main difference between the two spontaneous pressure control modes lies in the inspiratory phase; expiratory control is the same. Currently, clinical evidence shows that PAV mode offers greater patient comfort than PSV mode. The reasons for PAV mode's greater comfort compared to PSV mode are twofold: firstly, patients have greater freedom to control each inspiratory breath in PAV mode; secondly, the inspiratory flow waveform in PAV mode is closer to the approximate sine wave shape of natural breathing (see...). Figure 1 (This is different from the inhalation deceleration wave shape in PSV mode.)

[0057] Currently, regardless of the brand, proportional pressure assist PAV mode has three obvious drawbacks:

[0058] (1) Each mode needs to know the patient’s airway resistance and lung elasticity. These respiratory mechanics parameters are either guessed by the user or identified online by the ventilator. In fact, due to the patient’s voluntary effort during spontaneous ventilation, it is almost impossible to obtain reliable respiratory mechanics parameters. Moreover, in reality, the actual respiratory mechanics is very complex and there are no linear respiratory mechanics parameters available for identification.

[0059] (2) Each mode requires the user to set (titrate) the auxiliary coefficient, but there is no simple method to guide the user to set this key auxiliary coefficient. If the auxiliary coefficient is set too low, the patient will become fatigued; conversely, if the auxiliary coefficient is set too high, the patient will become respiratory dependent or even experience airflow escape.

[0060] (3) In PAV mode, it is impossible to control key respiratory indicators such as tidal volume, minute ventilation, and respiratory rate as in conventional mode. Therefore, in PAV mode, the patient's respiratory indicators are actually in an uncontrolled state. This reflects the difference between this positive feedback mechanism mode and the conventional negative feedback mechanism mode. This huge difference makes ventilator operators feel helpless because they are more familiar with conventional negative feedback mechanism ventilation modes, that is, those ventilation modes that use fixed pressure, tidal volume, minute ventilation, or respiratory rate as control targets. This is also an important factor that prevents PAV mode from being clinically promoted.

[0061] Based on this, embodiments of this application provide a method and apparatus for adjusting PAV parameters of a ventilator to solve the above-mentioned problems.

[0062] The various embodiments of this application are described in detail below with reference to the accompanying drawings.

[0063] Figure 2 This is a schematic diagram of the structure of the ventilator according to an embodiment of this application, as shown below. Figure 2 As shown, the ventilator includes an air source 110, an airway structure 120 connected to it, and the airway structure 120 connected to the patient interface 140 via tubing 130. It also includes a drive and detection circuit 150, a ventilation controller 160, a human-machine interface 170, external devices 180, and a power supply unit 190. External devices are devices connected to the ventilator, such as external displays, etc., and this application does not specifically limit their use.

[0064] The specific structural diagram of the gas path structure 120 is as follows: Figure 3 As shown, the system includes: an air filter 1, an oxygen valve 2, an oxygen flow sensor 3, an oxygen mixing chamber 4, an oxygen concentration sensor 5, a turbine 6, an inhalation valve 7, an inhalation flow sensor 8, an inhalation pressure sensor 9, an expiratory flow probe 10, an expiratory pressure sensor 11, an expiratory flow sensor 12, and an expiratory valve 13. The inhalation flow sensor 8 and the expiratory flow probe 10 are connected to a conduit 130, which includes a bacterial filter 14 in the inhalation conduit, a bacterial filter 15 in the expiratory conduit, and a humidifier 16 in the inhalation conduit.

[0065] During actual use of the ventilator, air passes through air filter 1 and enters the mixing chamber 4 inside the machine, where it mixes with oxygen from a high-pressure gas source. The high-pressure oxygen enters the mixing chamber 4 through oxygen valve 2 and oxygen flow sensor 3. Oxygen valve 2 adjusts the oxygen flow rate, and oxygen flow sensor 3 monitors the flow rate. The mixed gas entering the mixing chamber 4 is pressurized by turbine 6 and then enters the front end of inspiratory valve 7. Inspiratory valve 7 adjusts the mixed airflow and, after being monitored by inspiratory flow sensor 8 and inspiratory pressure sensor 9, outputs it to the external inspiratory tubing of the ventilator. The tubing is connected to a bacterial filter 14 and a humidifier 16, which provide cleaning, heating, and humidification. An oxygen concentration sensor 5 is also connected in parallel between the output end of turbine 6 and the inlet end of mixing chamber 4 to monitor the actual oxygen concentration in the tubing. The patient's exhaled gas can re-enter the machine through the exhalation tubing and bacterial filter 15, and be discharged into the atmosphere by the machine. Before being discharged into the atmosphere, the exhaled gas is monitored by the exhalation pressure sensor 11 and flows through the exhalation flow probe 10 and the exhalation valve 13. The exhalation flow sensor 12 connected in parallel with the exhalation flow probe 10 can be a differential pressure sensor.

[0066] In the embodiments of this application, the schematic diagram of the ventilator described above is a dual-limb breathing circuit structure. The ventilator used in this application is not limited to the ventilator with the above structure, but can also be applied to ventilators with a single-limb breathing circuit structure. The ventilation interface connecting to the patient is not limited to invasive interfaces such as intubation, but can also be non-invasive ventilation interfaces such as face masks and nasal plugs.

[0067] In this embodiment, the airway structure includes a turbine, so a high-pressure air source is not required. This embodiment is not limited to the above structure, and can also be used in ventilator airway structure systems that do not have a built-in turbine and rely on a high-pressure air source for air supply.

[0068] In the above-described air circuit structure of this application, there is an intake valve at the rear end of the turbine for adjusting the intake flow rate and pressure. However, this intake valve can also be omitted in specific embodiments, and the intake flow rate and pressure can be directly adjusted by the rapid acceleration and deceleration of the turbine.

[0069] In this embodiment of the application, the above-mentioned expiratory flow sensor is a differential pressure type. This application is not limited to differential pressure expiratory flow sensors, but can also be a thermal flow sensor.

[0070] In the embodiments of this application, the oxygen concentration sensor in the gas path structure can be an electrochemical oxygen cell, an ultrasonic oxygen concentration sensor, or a paramagnetic oxygen concentration sensor; this application does not specifically limit the type of sensor.

[0071] This application provides a method for adjusting PAV parameters in a ventilator, wherein the method is executed by the aforementioned... Figure 2The ventilation controller in this application can be an MCU, PLC, or a server, server cluster, or computer connected to the ventilator; this application does not specifically limit its application in this regard. The ventilation controller can receive various ventilation detection signals from the drive and detection circuits, such as flow rate and pressure. After processing, the ventilation detection signals can output various respiratory monitoring parameters, including but not limited to tidal volume, respiratory rate, minute ventilation, peak inspiratory pressure, and positive end-expiratory pressure. The ventilation controller can also, through the drive and detection circuits, establish control and / or be controlled relationships with various valves and turbines in the airway structure. Figure 4 As shown, the method for adjusting PAV parameters for a ventilator may include steps S401-S404:

[0072] S401, based on a predetermined sinusoidal flow ventilation waveform, determine multiple pre-ventilation characteristic parameter sets and their corresponding initial proportional auxiliary ventilation (PAV) parameter sets corresponding to a preset output time of the sinusoidal flow ventilation waveform.

[0073] The predetermined sinusoidal flow ventilation waveform is the output waveform preset in the ventilation controller. The sinusoidal flow ventilation waveform in this application is a sinusoidal flow waveform in capacitive control mode. Ventilation using the predetermined sinusoidal flow ventilation waveform constitutes the pre-ventilation stage. The waveform of the capacitive control sinusoidal ventilation is as follows: Figure 5 As shown, the target formula for the inhalation flow rate of the sinusoidal flow ventilation waveform is:

[0074] F(t)=(VT_set*pi) / (2*Ti)*sin(t*pi / Ti)

[0075] Where F(t) is the flow rate, VT_set is the target tidal volume set by the user through the human-computer interaction interface before pre-ventilation, pi is the mathematical constant π, Ti is the inspiratory time of pre-ventilation, Ti is related to the set target respiratory rate, and t is the time in seconds.

[0076] When the inspiratory-to-expiratory ratio is 1:2, the above Ti = 20 / RR_set, where RR_set is the target respiratory rate set by the user through the human-computer interaction interface, in breaths per minute.

[0077] The preset output time includes multiple respiratory cycles of the patient, such as 3-6 breaths. Within the preset output time, the ventilator outputs a flow rate using a sinusoidal flow-frequency waveform, and the ventilation controller collects characteristic parameters during each breath, forming a pre-ventilation characteristic parameter set. (Reference) Figure 5The pre-ventilation characteristic parameter set includes: peak inspiratory pressure Ppeak under volume-controlled sinusoidal ventilation (pre-ventilation), end-inspiratory pressure Peip under volume-controlled sinusoidal ventilation, measured tidal volume VT, measured positive end-expiratory pressure PEEP, and flow rate F1 and volume V1 at the time point corresponding to peak inspiratory pressure Ppeak. Since a set of pre-ventilation characteristic parameters is obtained for each breath, multiple sets of characteristic parameters can be used to solve for multiple sets of PAV parameters.

[0078] In this embodiment of the application, based on a predetermined sinusoidal flow ventilation waveform, multiple pre-ventilation characteristic parameter sets corresponding to a preset output time of the sinusoidal flow ventilation waveform and their corresponding initial proportional auxiliary ventilation (PAV) parameter sets are determined, specifically including:

[0079] First, the ventilation controller generates a pre-ventilation trigger signal, which causes the ventilator to supply pressurized gas with a sinusoidal flow rate for a preset output time. This preset output time includes at least the time required for the patient to receive a preset number of breaths.

[0080] Next, the pre-ventilation detection information for each breath within a preset output time is determined through the flow and sensing modules (oxygen flow sensor 3, oxygen concentration sensor 5, inspiratory flow sensor 8, inspiratory pressure sensor 9, inspiratory pressure sensor 11, and expiratory flow sensor 12). The pre-ventilation detection information includes at least: flow rate, pressure, respiratory initiation time, and respiratory termination time.

[0081] Subsequently, the pre-ventilation detection information was analyzed, and the pre-ventilation characteristic parameter set corresponding to each breath was determined.

[0082] Specifically, such as Figure 5 The ventilation controller first determines the inspiratory pressure data from the pre-ventilation detection information, and then determines the peak inspiratory pressure Ppeak and the end-inspiratory pressure Peip from the inspiratory pressure data. It also determines the positive end-expiratory pressure PEEP and tidal volume VT from the pre-ventilation detection information.

[0083] Specifically, determining the tidal volume in the pre-ventilation detection information includes:

[0084] like Figure 5 The volume curve in the test, with the start time of respiration as the starting point and the end time of respiration as the ending point, integrates the flow rate of the pre-ventilation detection information corresponding to one respiration to determine the maximum and minimum inspiratory volume values ​​of one respiration.

[0085] The initial tidal volume corresponding to one breath is determined based on the maximum inspiratory volume, the minimum inspiratory volume, and the first preset formula.

[0086] The first preset formula is as follows:

[0087] VTi=(2×Vmax-Vmin) / 2

[0088] The above VTi represents the tidal volume in the i-th breath, Vmax represents the maximum inspiratory volume, and Vmin represents the minimum inspiratory volume.

[0089] Calculate the moving average of the initial tidal volume for each breath in the pre-ventilation detection information, and use the moving average as the tidal volume in the pre-ventilation detection information.

[0090] In other words, based on the number of breaths during pre-ventilation, the moving average of the tidal volume of multiple breaths is calculated as the tidal volume during the pre-ventilation phase, such as: VT_real=ΣVTi / n, where VT_real is the tidal volume in the pre-ventilation detection information.

[0091] Based on the preset initial PAV parameters, the model is determined, and the set of undetermined PAV parameters corresponding to each pre-ventilation characteristic parameter group is determined. The set of undetermined PAV parameters includes at least capacity auxiliary parameters and flow auxiliary parameters.

[0092] Specifically, the model, end-inspiratory pressure, positive end-expiratory pressure, and tidal volume are determined based on the initial PAV parameters, and volume auxiliary parameters are determined accordingly.

[0093] Substitute the end-inspiratory pressure (IIP), end-expiratory pressure (EEAP), and tidal volume into the initial PAV parameters to determine the formula for calculating the model's volume auxiliary parameters:

[0094] KV(T0)=(Peip-PEEP) / VT

[0095] Wherein, KV(T0) is the volume auxiliary parameter during the T0th breath.

[0096] Substitute the peak inspiratory pressure Ppeak, volume auxiliary parameter KV(T0), positive end-expiratory pressure PEEP, and flow data F1 and volume data V1 at the corresponding moment of peak inspiratory pressure into the flow auxiliary parameter calculation formula to determine the flow auxiliary parameter.

[0097] Flow auxiliary parameter calculation formula: KF(T0)=(Ppeak-KV(T0)*V1-PEEP) / F1

[0098] Wherein, KF(T0) is the flow assist parameter during the T0th breath.

[0099] Based on each set of undetermined PAV parameters, determine the initial set of PAV parameters.

[0100] During the pre-ventilation phase (3-6 breaths), multiple sets of undetermined PAV parameters can be obtained, such as {KV(T0), KF(T0)}, {KV(T1), KF(T1)}, etc. Based on the obtained sets of undetermined PAV parameters, the average values ​​of the volume auxiliary parameters and flow auxiliary parameters are calculated to obtain the initial PAV parameter set {KV(T), KF(T)}.

[0101] S402, when PAV ventilation is performed with the initial PAV parameter set, ventilation detection information is obtained from the flow and sensing module.

[0102] The ventilation monitoring information refers to the monitoring data obtained when the ventilator is operating in PAV mode. The monitoring data includes at least one or more of the following: flow rate and pressure.

[0103] After obtaining the initial PAV parameter set, the ventilator will output the gas mixture using the initial PAV parameter set. The pressure target of the ventilator at each inspiratory time point during the patient's breathing process is:

[0104] Ptarget(t)=KF(T)*F(t)+KV(T)*V(t)+PEEP

[0105] Where Ptarget(t) is the pressure value at time point t, and V(t) is the capacity value at time point t, which can be obtained by integrating the flow rate.

[0106] During ventilation, the ventilation controller can acquire flow and pressure data in real time.

[0107] S403, based on ventilation detection information and preset auxiliary ventilation information, matches a preset parameter update strategy to update the initial PAV parameter set according to the parameter update strategy.

[0108] In this embodiment of the application, based on ventilation detection information and preset assisted ventilation information, a preset parameter update strategy is matched, specifically including:

[0109] Determine the reciprocal of the difference between the time of respiratory termination and the time of respiratory initiation for each of the historical predetermined number of continuous breaths in the ventilation detection information.

[0110] The historical pre-set number of breaths refers to the pre-set number of breaths prior to the current breath. The historical pre-set number of breaths can be set by the user, and this application does not specify a particular value for this pre-set number of breaths.

[0111] Calculate the product of the reciprocal of each difference and a predetermined unit of time, and use each product as the single respiratory rate for each breath. Then, use the moving average of each single respiratory rate as the respiratory rate value for the current breath.

[0112] In other words, the moving average of the single-breath frequency of a predetermined number of breaths in the past can be used as the respiratory frequency value of the current breath. For example, at the beginning of each inhalation (that is, the end time te of the previous breath), the duration of the previous breath Tie = te - t0 is calculated, and the reciprocal of the duration of one breath Tie (in seconds) is multiplied by 60 to obtain the current frequency RRi of this breath. The frequency of the previous predetermined number of breaths (n times) can be taken as the respiratory frequency RR_real, that is, RR_real = ΣRRi / n.

[0113] Next, based on the flow rate from the ventilation monitoring information, the tidal volume of the current breath is determined.

[0114] The method for calculating tidal volume has been described in detail in the specific embodiment of S401 above, and will not be repeated here.

[0115] Then, based on the matching results of respiratory rate, tidal volume, and assisted ventilation information, a corresponding parameter update strategy is determined. The assisted ventilation information includes preset target respiratory rate and target tidal volume.

[0116] Specifically, a Cartesian coordinate system is established with respiratory rate (RR) as the horizontal axis and respiratory volume (VT) as the vertical axis.

[0117] Based on the target respiratory rate, target tidal volume, and preset multiple level interval division parameters of the assisted ventilation information, multiple level interval division neighborhoods are generated, consisting of different level interval division parameters, target respiratory rate, and target tidal volume.

[0118] The target respiratory rate and target tidal volume are both set by the user before the pre-ventilation phase. The corresponding zones for each level are: moderate, poor, and poor. The state space composed of volume / frequency is divided into three regions: the first region (moderate) is very close to the target volume / frequency; the second region (poor) and the third region (poor) move further away from the target state values ​​(target respiratory rate and target tidal volume). The specific rules for dividing these three regions are as follows:

[0119] Suitable area:

[0120] 75%*VT_set≤VT_real≤150%*VT_set;

[0121] and

[0122] 75%*RR_set≤RR_real≤150%*RR_set;

[0123] Moderately poor areas:

[0124] 150% * VT_set <VT_real≤200%*VT_set;

[0125] or

[0126] 50%*VT_set≤VT_real<75%*VT_set;

[0127] or

[0128] 150%*RR_set <RR_real≤200%*RR_set;

[0129] or

[0130] 50%*RR_set≤RR_real<75%*RR_set;

[0131] Areas with poor height:

[0132] VT_real > 200% * VT_set;

[0133] or

[0134] VT_real < 50% * VT_set;

[0135] or

[0136] RR_real > 200% * RR_set;

[0137] or

[0138] RR_real < 50% * RR_set;

[0139] VT_real and RR_real are the measured tidal volume and respiratory rate values ​​of the current breath, respectively, while VT_set and RR_set are the target tidal volume and target respiratory rate values, respectively.

[0140] Based on the division of neighborhoods according to each level interval, the level interval division regions are generated in a Cartesian coordinate system as follows: Figure 6 As shown in the figure. The figure includes a moderate area 601, a moderately poor area 602, a highly poor area 603, and a target point 604 corresponding to the target tidal volume and target respiratory rate values.

[0141] The ventilation controller determines the corresponding coordinate matching ranges for respiratory rate and tidal volume, and then determines a preset parameter update strategy based on these matching ranges. The parameter update strategy includes the adjustment range and direction of parameters within the PAV parameter set.

[0142] The parameter update strategy can be pre-stored in the ventilation controller or stored in an external database connected to the ventilation controller via a network or wired connection. The specific parameter update strategy can be set by the user. For example, in the moderate range, the adjustment is very small (slow adjustment), such as only a 10% adjustment based on the previous value; in the moderately poor range, the adjustment is larger (medium-speed adjustment), such as a 50% adjustment based on the previous value; in the height-poor range, the adjustment is maximum (fast adjustment), such as a 200% adjustment based on the previous value.

[0143] If the adjustment range for each iteration is Δ%, then the auxiliary parameters corresponding to each respiratory update after the parameter adjustment range formula are:

[0144] KF(T)=KF(T-1)*(1±Δ%)

[0145] KV(T)=KV(T-1)*(1±Δ%)

[0146] In KF(T-1) and KV(T-1), T-1 represents the auxiliary parameter in the previous breath.

[0147] The auxiliary parameter adjustment principle proposed in this application is simple and easy to implement. It involves two auxiliary coefficients: a volume auxiliary coefficient (KV) and a flow auxiliary coefficient (KF). Their adjustment is decoupled, meaning that their adjustment depends only on their respective individual state variables. The adjustment of the volume auxiliary coefficient (KV) depends on the tidal volume (VT), while the adjustment of the flow auxiliary coefficient (KF) depends on the respiratory rate (RR).

[0148] Rules for adjusting capacity auxiliary parameters:

[0149] If VT_real is lower than VT_set, then KV is increased, i.e., the adjustment range formula above is KV(T)=KV(T-1)*(1+Δ%);

[0150] If VT_real is higher than VT_set, then KV is lowered, i.e., the above adjustment formula is: KV(T)=KV(T-1)*(1-Δ%);

[0151] Rules for adjusting the direction of the flow auxiliary coefficient parameters:

[0152] If RR_real is lower than RR_set, then KF is increased, i.e., KF(T) = KF(T-1)*(1+Δ%);

[0153] If RR_real is higher than RR_set, then KF is lowered, KF(T) = KF(T-1)*(1-Δ%);

[0154] The above example illustrates the case where Δ% is a positive value. Those skilled in the art will understand that if Δ% is a negative value, the sign in the formula corresponding to the above adjustment rule will be the opposite of when Δ% is a positive value.

[0155] In this application embodiment, the updated PAV parameter set generates PAV control commands to control the corresponding pressure value of the ventilator's PAV mode (Ptarget(t) = KF(T)*F(t) + KV(T)*V(t) + PEEP) in real time according to the updated PAV parameter set. During the patient's breathing process, respiratory flow and pressure are time-varying, and the updated PAV parameter set may be unreasonable, requiring real-time adjustment. This application provides the following embodiments, specifically including:

[0156] The updated PAV parameter set is used as the initial PAV parameter set, and PAV ventilation is performed using the updated initial PAV parameter set to obtain the corresponding ventilation detection information.

[0157] Then, based on the matching results of ventilation detection information and assisted ventilation information corresponding to each breath, it is determined whether the parameters in the initial PAV parameter set are parameters to be updated.

[0158] In other words, after updating the initial PAV parameter set, ventilation can be resumed with the updated initial PAV parameters, and ventilation detection information can be acquired. Following the specific implementation of the parameter update strategy described above, the ventilation detection information and assisted ventilation information are matched in real time to determine if a matching parameter update strategy is found. If a matching parameter update strategy is found, then the parameters in the current initial PAV parameter set are the parameters to be updated.

[0159] If the parameters in the initial PAV parameter set are determined to be the parameters to be updated, the parameters in the initial PAV parameter set are updated before each breath begins until the matching results of the respiratory rate, tidal volume and assisted ventilation information corresponding to the ventilation detection information meet the preset conditions.

[0160] The preset conditions are that the absolute values ​​of the differences between the respiratory rate and the target respiratory rate, and the tidal volume and the target tidal volume, are less than preset values. These preset values ​​are set by the user and can be understood as error values ​​within an acceptable range; this application does not specify any particular limitation on the preset values.

[0161] In the embodiments of this application, the auxiliary parameters provided above have two possibilities: increasing or decreasing. Each adjustment also has three possibilities: slow, medium, and fast. That is to say, there are 2*3=6 possibilities for adjusting each auxiliary coefficient.

[0162] The rules for adjusting the volume auxiliary parameters are indisputable: if the tidal volume is low, the volume auxiliary pressure should be increased, and vice versa.

[0163] The adjustment rules for flow assist parameters are explained as follows: With a fixed tidal volume and inspiratory-expiratory ratio, a high respiratory rate results in a shorter inspiratory time and a correspondingly higher average inspiratory flow rate; conversely, a low respiratory rate results in a longer inspiratory time and a correspondingly lower average inspiratory flow rate. Therefore, it can be deduced that a high respiratory rate is very likely caused by a high average inspiratory flow rate, and similarly, a low respiratory rate is very likely caused by a low average inspiratory flow rate. Thus, when the respiratory rate is higher than the target value, lowering the flow assist parameter aims to reduce the average inspiratory flow rate (to make the inspiratory flow waveform smoother) and bring the respiratory rate closer to the target value; conversely, when the respiratory rate is lower than the target value, increasing the flow assist parameter is reasonable.

[0164] In other words, for patients with high airway resistance (such as those with chronic obstructive pulmonary disease (COPD), their respiratory rate is more likely to be slower than normal, and the flow assist factor will be increased accordingly (to deliver air faster and inspiratory flow higher); while for patients with low airway resistance (such as those with acute respiratory distress syndrome (ARDS), their respiratory rate is more likely to be faster than normal, and the flow assist factor will be decreased accordingly (to deliver air slower and inspiratory flow more moderate). These are consistent with actual clinical experience in mechanical ventilation.

[0165] S404 generates PAV control commands based on the updated PAV parameter set, so as to control the corresponding pressure value of the ventilator's PAV mode in real time according to the updated PAV parameter set.

[0166] In this application embodiment, based on the updated

[0167] The PAV parameter set is used to generate PAV control commands, which are then used to control the corresponding pressure values ​​of the ventilator's PAV mode in real time based on the updated PAV parameter set. Specifically, this includes:

[0168] After generating the PAV control command, the undetermined pressure value and the undetermined pressure change curve are determined according to the second preset formula, using the PAV parameter set as the output.

[0169] The second preset formula is Ptarget(t)=KF(T)*F(t)+KV(T)*V(t)+PEEP.

[0170] Inspiratory pressure is a time-varying target, directly proportional to both flow rate F(t) and volume V(t) at each moment. This application can employ a pressure controller to monitor respiratory pressure.

[0171] Before inputting Ptarget(t) into the pressure tracking controller, each undetermined pressure value in the undetermined pressure change curve is limited and adjusted based on the slope value, the extreme pressure value corresponding to the extreme point of the undetermined pressure change curve, and the corresponding limit values. These limited and adjusted undetermined pressure values ​​are then input into the ventilator's pressure controller to control the corresponding pressure value in the ventilator's PAV mode in real time. The limit values ​​include slope limit and maximum value limit. These limit values ​​are used to adjust the numerical value of each undetermined pressure value.

[0172] The aforementioned slope and maximum value limits are preset by the user. The slope limit refers to the fact that if the pressure rises too quickly, it will not only exceed the actuator's capacity but also cause discomfort such as over-inhalation in the patient. Therefore, it is necessary to limit the rate of pressure increase. Specifically, this means limiting the increase in pressure target from the previous actual pressure target to a certain reasonable value, i.e., providing a slope limit.

[0173] The maximum limit is also for safety reasons; the pressure target must not exceed the ventilator's pressure alarm limit. In practice, if the calculated pressure target value exceeds the maximum limit (but is lower than the pressure alarm limit), the target value Ptarget(t) should be set equal to the maximum limit.

[0174] The aforementioned pressure controller (pressure tracking controller) can be constructed using various control theories, including but not limited to feedforward control, PID control, adaptive control, robust control, and combinations thereof. This application does not specifically limit its application in this regard.

[0175] In this application embodiment, the pressure control flowchart of the above-described pressure value control embodiment, namely the pressure control of proportional pressure assisted ventilation (PAV), is as follows: Figure 7 Shown, including:

[0176] The flow and sensing module performs pressure detection (702) and flow detection (703) from the ventilation line (701). It then compares the measured pressure (Preal) with the pressure target after slope and maximum value limits (704), integrates the flow rate to obtain the capacity (V(t),) performs capacity monitoring (705), and generates a pressure target (706) from the capacity (V(t)) and flow rate (F(t)). Pressure target generation (706) calculates the pressure target (Ptarget(t)) based on the flow rate (F(t)) and capacity (V(t)). Next, the pressure target is subjected to slope and maximum value limits (707), and the pressure target processed by slope and maximum value limits (707) is compared with the measured pressure (Preal) (704). This data is then input to the pressure tracking controller (708), which also includes the flow rate (F(t)) and capacity (V(t)). The pressure tracking controller 708 adjusts the pressure target size, such as setting the target value Ptarget(t) to equal the maximum limit, and adjusts the pressure slope value, based on the analysis and control results of the pressure target. In turn, it controls the turbine or proportional valve 709 to adjust the output pressure value of the ventilator and provides mixed gas to the patient 7010 through the ventilation line 701.

[0177] In this embodiment, after updating the PAV parameter set, the PAV parameter sets corresponding to a preset number of breaths and the parameter update direction of each PAV parameter set are determined. The parameter update direction includes a positive update direction and a negative update direction. Based on the parameter update direction and the change in parameter distance between each parameter in the PAV parameter set and the corresponding parameter in the assisted ventilation information, the parameter update direction of the current breath is updated, and the PAV parameter set is updated.

[0178] In other words, during real-time monitoring of PAV parameters, the adjustment trend can be monitored. If the adjustment of PAV parameters fails to approach the final target as expected, but instead deviates from the target—that is, if tidal volume and respiratory rate do not approach the target tidal volume and respiratory rate after adjusting PAV parameters—then this application can stop adjusting PAV parameters, or even adjust PAV parameters in the opposite direction. For example, instead of increasing PAV parameters, the application can decrease PAV parameter values.

[0179] Furthermore, if the target tidal volume and target respiratory rate cannot be approached after multiple adjustments, this application can issue an alarm signal, such as an audio or text message. If multiple adjustments are ineffective, returning to the initial capacitive sinusoidal pre-ventilation control is also a reasonable option, and this application does not specifically limit this choice.

[0180] In one embodiment of this application, the value range of each auxiliary parameter (capacity auxiliary parameter, flow auxiliary parameter) should have a maximum and minimum limit for any adjustment, and the adjustment range of these auxiliary coefficients should also be different for different patient groups, such as adults and children. The limit of their value range is set by the user, who can set it independently according to adults, children, or different physical conditions. This application does not make specific limitations in this regard.

[0181] The PAV parameter adjustment method for a ventilator provided in the embodiments of this application, Figure 8 A flowchart illustrating the usage of PAV parameter adjustment is provided, such as... Figure 8 As shown, it specifically includes:

[0182] S801, set the target tidal volume VT_set and the target respiratory rate RR_set;

[0183] S802, Capacitively controlled sinusoidal wave test ventilation;

[0184] S803, measure the initial auxiliary parameters KF(T0) and KV(T0);

[0185] S804, proportional pressure assisted ventilation (PAV);

[0186] S805 monitors the actual tidal volume VT_real and respiratory rate RR_real;

[0187] S806 automatically adjusts auxiliary parameters KF(T) and KV(T);

[0188] S807, adjusts abnormal handling and alarms.

[0189] As mentioned above, this includes updating the current breathing parameters in the correct direction and issuing alarm signals.

[0190] This application, through the aforementioned scheme, outputs a sinusoidal flow ventilation waveform during pre-ventilation, allowing users to obtain initial PAV parameters without needing to guess the patient's airway resistance and lung elasticity, or set auxiliary proportional parameters. Furthermore, this application uses familiar tidal volume and respiratory rate as control targets, automatically adjusting the auxiliary parameters (volume auxiliary parameters and flow auxiliary parameters) of proportional pressure assisted ventilation (PAV) in three levels (slow, medium, and fast) based on the actual tidal volume and respiratory rate monitored for each breath, and their position in the respiratory state space. This ensures the patient's freedom to control tidal volume and respiratory rate independently.

[0191] The flow-assisted and volume-assisted parameters mentioned above are decoupled. The flow-assisted parameter is adjusted to bring the actual respiratory rate closer to the set respiratory rate; the volume-assisted parameter is adjusted to bring the actual tidal volume closer to the set tidal volume. This overcomes the shortcomings of existing proportional pressure-assisted modes, where users have no basis for setting mode parameters. The new mode is more in line with users' conventional thinking when setting ventilation modes. Users do not need to know difficult-to-understand respiratory mechanics parameters such as airway resistance and lung compliance; the mode is effective and easy to understand.

[0192] The ventilator with PAV parameter adjustment provided in this application achieves the clinical goal of targeted control while ensuring the patient remains in a comfortable and safe ventilation state. Furthermore, the auxiliary parameters for each breath are based on the auxiliary parameters of the previous breath, making PAV parameter adjustment more scientific. By combining negative and positive feedback mechanisms for PAV parameter adjustment, the ventilator with PAV parameter adjustment provided in this application offers safer, more comfortable, and easier-to-use benefits for patients, improving their experience with the ventilator's PAV mode.

[0193] Figure 9 A schematic diagram of a PAV parameter adjustment device for a ventilator provided in this application embodiment is shown. The device includes:

[0194] The determination module 901 is used to determine, based on a predetermined sinusoidal flow ventilation waveform, multiple pre-ventilation characteristic parameter sets corresponding to a preset output time of the sinusoidal flow ventilation waveform and their corresponding initial proportional auxiliary ventilation (PAV) parameter sets.

[0195] The acquisition module 902 is used to acquire ventilation detection information from the flow and sensing module when PAV ventilation is performed with an initial PAV parameter set. The ventilation detection information is the detection information obtained when the ventilator is in PAV mode. The detection information includes at least one or more of the following: flow rate and pressure.

[0196] The matching module 903 is used to match a preset parameter update strategy based on ventilation detection information and preset auxiliary ventilation information, so as to update the initial PAV parameter set according to the parameter update strategy.

[0197] The generation module 904 is used to generate PAV control commands based on the updated PAV parameter set, so as to control the corresponding pressure value of the ventilator's PAV mode in real time according to the updated PAV parameter set.

[0198] Module 901 is specifically used for:

[0199] A pre-ventilation trigger signal is generated to enable the ventilator to supply pressurized gas with a sinusoidal flow rate for a preset output time. The preset output time includes at least the time required for the patient to receive a preset number of breaths.

[0200] The flow and sensing modules determine the pre-ventilation detection information for each breath within a preset output time. The pre-ventilation detection information includes at least: flow rate, pressure, respiratory initiation time, and respiratory termination time.

[0201] Analyze the pre-ventilation detection information and determine the pre-ventilation characteristic parameter set corresponding to each breath.

[0202] Based on the preset initial PAV parameters, the model is determined, and the set of undetermined PAV parameters corresponding to each pre-ventilation characteristic parameter group is determined. The set of undetermined PAV parameters includes at least capacity auxiliary parameters and flow auxiliary parameters.

[0203] Based on each set of undetermined PAV parameters, determine the initial set of PAV parameters.

[0204] Module 901 is specifically used for:

[0205] Determine the inspiratory pressure data from the pre-ventilation detection information, and determine the peak inspiratory pressure and terminal inspiratory pressure values ​​from the inspiratory pressure data.

[0206] Determine the positive end-expiratory pressure and tidal volume in the pre-ventilation detection information.

[0207] The model is determined based on the preset initial PAV parameters, and the set of undetermined PAV parameters corresponding to each pre-ventilation characteristic parameter group is determined, specifically including:

[0208] Volume auxiliary parameters are determined based on the end-inspiratory pressure, positive end-expiratory pressure, and tidal volume.

[0209] The flow auxiliary parameters are determined based on the peak inspiratory pressure, volume auxiliary parameters, positive end-expiratory pressure, and flow and volume data at the corresponding time of the peak inspiratory pressure.

[0210] Module 901 is specifically used for:

[0211] Starting from the moment of inhalation and ending at the moment of respiration, the flow rate of the pre-ventilation detection information corresponding to one breath is integrated to determine the maximum and minimum inspiratory volume values ​​for one breath.

[0212] The initial tidal volume corresponding to one breath is determined based on the maximum inspiratory volume, the minimum inspiratory volume, and the first preset formula.

[0213] Calculate the moving average of the initial tidal volume for each breath in the pre-ventilation detection information, and use the moving average as the tidal volume in the pre-ventilation detection information.

[0214] Matching module 903 is specifically used for:

[0215] Determine the number of consecutive breaths in the historical predetermined number of breaths from the ventilation monitoring information, and the reciprocal of the difference between the end time and the start time of each breath. The historical predetermined number of breaths refers to the predetermined number of breaths prior to the current breath.

[0216] Calculate the product of the reciprocal of each difference and a predetermined unit of time, and use each product as the single respiratory rate for each breath. Then, use the moving average of each single respiratory rate as the respiratory rate value for the current breath.

[0217] Based on the flow rate from ventilation monitoring information, the tidal volume of the current breath is determined.

[0218] Based on the matching results of respiratory rate, tidal volume, and assisted ventilation information, a corresponding parameter update strategy is determined. The assisted ventilation information includes preset target respiratory rate and target tidal volume.

[0219] Matching module 903 is specifically used for:

[0220] Establish a Cartesian coordinate system with respiratory rate as the x-axis and respiratory volume as the y-axis.

[0221] Based on the target respiratory rate, target tidal volume, and preset multiple level interval division parameters of the assisted ventilation information, multiple level interval division neighborhoods are generated, consisting of different level interval division parameters, target respiratory rate, and target tidal volume.

[0222] Based on the division of neighborhoods according to each level interval, the level interval division region is generated in a Cartesian coordinate system.

[0223] The coordinate matching intervals for respiratory rate and tidal volume are determined, and a preset parameter update strategy is determined based on these intervals. The parameter update strategy includes the adjustment range and direction of parameters within the PAV parameter set.

[0224] Matching module 903 is also used for:

[0225] The updated PAV parameter set is used as the initial PAV parameter set, and PAV ventilation is performed using the updated initial PAV parameter set to obtain the corresponding ventilation detection information.

[0226] Based on the matching results of ventilation detection information and assisted ventilation information corresponding to each breath, determine whether the parameters in the initial PAV parameter set are parameters to be updated.

[0227] If so, before each breath begins, update the parameters in the initial PAV parameter set until the matching results of the respiratory rate, tidal volume, and assisted ventilation information corresponding to the ventilation detection information meet the preset conditions. The preset conditions are that the absolute values ​​of the differences between the respiratory rate and the target respiratory rate, and the tidal volume and the target tidal volume, are less than preset values.

[0228] Module 904 is specifically used for:

[0229] After generating the PAV control command, the undetermined pressure value and the undetermined pressure change curve are determined according to the second preset formula, using the PAV parameter set as the output.

[0230] Based on the slope of the pressure change curve, the extreme pressure values ​​corresponding to the extreme points of the curve, and the corresponding limits, the pressure values ​​in the curve are adjusted and limited. These adjusted pressure values ​​are then input to the ventilator's pressure controller to control the corresponding pressure values ​​in the ventilator's PAV mode in real time. The limits include slope limits and maximum value limits. These limits are used to adjust the values ​​of each pressure value.

[0231] The device also includes:

[0232] The parameter update determination module is used to determine the PAV parameter sets corresponding to the preset number of breaths and the parameter update direction for each PAV parameter set after updating the PAV parameter set. The parameter update direction includes positive update direction and negative update direction.

[0233] The parameter update direction update module is used to update the parameter update direction of the current breathing and update the PAV parameter set based on the parameter update direction and the change in parameter distance between each parameter in the PAV parameter set and the corresponding parameter in the assisted ventilation information.

[0234] The various embodiments in this application are described in a progressive manner. Similar or identical parts between embodiments can be referred to mutually. Each embodiment focuses on describing the differences from other embodiments. In particular, the device embodiments are basically similar to the method embodiments, so the description is relatively simple; relevant parts can be referred to the descriptions of the method embodiments.

[0235] The apparatus and method provided in this application are one-to-one correspondences. Therefore, the apparatus also has similar beneficial technical effects as its corresponding method. Since the beneficial technical effects of the method have been described in detail above, the beneficial technical effects of the apparatus will not be repeated here.

[0236] It should also be noted that the terms "comprising," "including," or any other variations thereof are 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. Without further limitation, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0237] The foregoing is merely an embodiment of the present application and is not intended to limit the present application. For those skilled in the art, the present application may have various changes and variations. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present application should all be included within the scope of the claims of the present application.

Claims

1. A PAV parameter adjustment device for a ventilator, characterized in that, The device includes: The determination module is used to determine, based on a predetermined sinusoidal flow ventilation waveform, multiple pre-ventilation characteristic parameter sets corresponding to a preset output time of the sinusoidal flow ventilation waveform and their corresponding initial PAV parameter sets. The acquisition module is used to acquire ventilation detection information from the flow and sensing module when PAV ventilation is performed with the initial PAV parameter set; wherein the ventilation detection information is the detection information when the ventilator is ventilated in PAV mode; the detection information includes one or more of the following: flow rate and pressure; The matching module is used to match a preset parameter update strategy based on the ventilation detection information and the preset auxiliary ventilation information, so as to update the initial PAV parameter set according to the parameter update strategy. The generation module is used to generate PAV control commands based on the updated PAV parameter set, so as to control the corresponding pressure value of the PAV mode of the ventilator in real time according to the updated PAV parameter set. The determination module is specifically used for: A pre-ventilation trigger signal is generated so that the ventilator supplies pressurized gas with the sinusoidal flow ventilation waveform within the preset output time; the preset output time includes at least the time for the patient to receive oxygen at a preset number of breaths. The flow rate and sensing module determines the pre-ventilation detection information for each breath within the preset output time; the pre-ventilation detection information includes at least: flow rate, pressure, breathing start time, and breathing end time; The pre-ventilation detection information is analyzed, and the pre-ventilation characteristic parameter set corresponding to each breath is determined; Based on the preset initial PAV parameters, a model is determined, and a set of undetermined PAV parameters corresponding to each of the pre-ventilation characteristic parameter groups is determined; the set of undetermined PAV parameters includes at least capacity auxiliary parameters and flow auxiliary parameters. Based on each of the aforementioned sets of undetermined PAV parameters, the initial set of PAV parameters is determined; Specifically, the determination module is also used for: Determine the inspiratory pressure data in the pre-ventilation detection information, and determine the peak inspiratory pressure and the terminal inspiratory pressure value in the inspiratory pressure data; and Determine the positive end-expiratory pressure and tidal volume in the pre-ventilation detection information; Based on the preset initial PAV parameters, the model is determined, and the set of undetermined PAV parameters corresponding to each of the pre-ventilation characteristic parameter groups is determined, specifically including: The volume auxiliary parameter is determined based on the terminal inspiratory pressure, the positive end-expiratory pressure, and the tidal volume. The flow assist parameter is determined based on the peak inspiratory pressure, the volume assist parameter, the positive end-expiratory pressure, and the flow rate and volume data at the time corresponding to the peak inspiratory pressure.

2. The apparatus according to claim 1, characterized in that, The module is also specifically used for: Starting from the time of the inhalation and ending from the time of the inhalation, the flow rate of the pre-ventilation detection information corresponding to one breath is integrated to determine the maximum and minimum inspiratory volume values ​​of one breath. The initial tidal volume corresponding to one breath is determined based on the maximum inspiratory volume value, the minimum inspiratory volume value, and the first preset formula. Calculate the moving average of the initial tidal volume corresponding to each breath in the pre-ventilation detection information, and use the moving average as the tidal volume in the pre-ventilation detection information.

3. The apparatus according to claim 1, characterized in that, The matching module is specifically used for: Determine the number of consecutive breaths in the ventilation detection information that is a predetermined number of times in the past, and the reciprocal of the difference between the end time and the start time of each breath; the predetermined number of times in the past refers to the predetermined number of breaths before the current breath. Calculate the product of the reciprocal of each difference and a predetermined unit of time, and use each product as the single respiratory rate of each breath; The moving average of each single respiratory rate is used as the respiratory rate value of the current breath. Based on the flow rate of the ventilation detection information, the tidal volume of the current breath is determined; Based on the matching results of the respiratory rate value, the tidal volume, and the assisted ventilation information, a corresponding parameter update strategy is determined; wherein, the assisted ventilation information includes a preset target respiratory rate value and a target tidal volume.

4. The apparatus according to claim 3, characterized in that, The matching module is also used for: Establish a Cartesian coordinate system with respiratory rate as the x-axis and respiratory volume as the y-axis; Based on the target respiratory rate, target tidal volume, and preset multiple level interval division parameters of the assisted ventilation information, multiple level interval division neighborhoods are generated, composed of different level interval division parameters, target respiratory rate, and target tidal volume. Based on the neighborhood division of each level interval, a level interval division region is generated in the Cartesian coordinate system. The coordinate matching level intervals corresponding to the respiratory rate value and the tidal volume are determined, and a preset parameter update strategy is determined based on the matching level intervals; the parameter update strategy includes the parameter adjustment amplitude and parameter adjustment direction in the PAV parameter set.

5. The apparatus according to claim 4, characterized in that, The matching module is also used for: The updated PAV parameter set is used as the initial PAV parameter set, and PAV ventilation is performed using the updated initial PAV parameter set to obtain the corresponding ventilation detection information. Based on the matching results of the ventilation detection information and the assisted ventilation information corresponding to each breath, determine whether the parameters in the initial PAV parameter set are parameters to be updated; If so, before each breath begins, update the parameters in the initial PAV parameter set until the matching result of the respiratory rate value, tidal volume and assisted ventilation information corresponding to the ventilation detection information meets the preset conditions; the preset conditions are that the absolute values ​​of the differences between the respiratory rate value and the target respiratory rate value and the tidal volume and the target tidal volume are less than the preset values.

6. The apparatus according to claim 1, characterized in that, The generation module is specifically used for: After generating the PAV control command, the undetermined pressure value and the undetermined pressure change curve output by the PAV parameter set are determined according to the second preset formula. Based on the slope value of the undetermined pressure change curve, the extreme pressure value corresponding to the extreme point of the undetermined pressure change curve, and the corresponding limit, the undetermined pressure values ​​in the undetermined pressure change curve are limited and adjusted so that the limited and adjusted undetermined pressure values ​​are input into the pressure controller of the ventilator to control the corresponding pressure value of the ventilator's PAV mode in real time; the limit includes a slope value limit and a maximum value limit; the limit is used to adjust the value of each undetermined pressure value.

7. The apparatus according to claim 1, characterized in that, The device can also: After updating the PAV parameter set, the PAV parameter set corresponding to the preset number of breaths and the parameter update direction of each PAV parameter set are determined; the parameter update direction includes positive update direction and negative update direction; Based on the parameter update direction and the change in parameter distance between each parameter in the PAV parameter set and the corresponding parameter in the assisted ventilation information, the parameter update direction of the current breathing is updated, and the PAV parameter set is updated.

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