CN116328122A

CN116328122A - Trigger threshold adjusting method and device, equipment and storage medium

Info

Publication number: CN116328122A
Application number: CN202310319171.XA
Authority: CN
Inventors: 晏凌聪; 黄飞翔; 何炜华
Original assignee: Shenzhen Comen Medical Instruments Co Ltd
Current assignee: Shenzhen Comen Medical Instruments Co Ltd
Priority date: 2023-03-22
Filing date: 2023-03-22
Publication date: 2023-06-27

Abstract

The embodiment of the invention discloses a method, a device, equipment and a storage medium for adjusting a trigger threshold, wherein the method comprises the following steps: acquiring a preset trigger threshold of the auxiliary breathing equipment and auxiliary ventilation data for reflecting the airway state of the auxiliary breathing equipment when the auxiliary breathing equipment performs auxiliary breathing on the basis of triggering of the preset trigger threshold; performing feature recognition of the human-machine state by using the auxiliary ventilation data, and determining a feature recognition result for reflecting the human-machine state of the auxiliary breathing equipment; when the feature recognition result comprises abnormal state features of which the man-machine states are asynchronous, performing feature quantization processing by using the abnormal state features, and determining an abnormal index for reflecting the countermeasure intensity of man-machine countermeasure caused by the abnormal state features; and adjusting the trigger threshold according to the abnormality index and a preset trigger threshold, and determining the adjusted trigger threshold. Through the mode, the trigger threshold is adjusted, the adjustment accuracy and efficiency are improved, and the man-machine synchronization speed is accelerated.

Description

Trigger threshold adjusting method and device, equipment and storage medium

Technical Field

The present invention relates to the field of assisted respiration technologies, and in particular, to a method, an apparatus, a device, and a storage medium for adjusting a trigger threshold.

Background

Auxiliary breathing apparatuses, such as ventilators, are important as effective apparatuses for replacing artificial spontaneous ventilation in therapeutic situations where respiratory support is required due to various conditions. However, during the mechanical ventilation process of the user using the ventilator, the man-machine countermeasure is a common problem in various types of ventilators, especially in the noninvasive ventilation process, the man-machine countermeasure situation is expressed more frequently, and the man-machine countermeasure often causes the problems that the user needs to take a larger dose of tranquilizer, breathing work is increased, circulation burden is increased, and the like, and even the life of the patient may be endangered when the countermeasure is serious.

In practical clinical application, because the instability of the user state is large, the fixed trigger threshold inevitably causes man-machine asynchronism, and proper trigger threshold needs frequent manual adjustment by medical staff with abundant experience according to the waveform characteristics of the breathing machine; in addition, in the automatic trigger threshold adjusting function adopted by the existing breathing machine, the man-machine countermeasure degree cannot be quantified well, the automatic adjustment of inhalation triggering and exhalation triggering is realized by adopting a fixed step adjusting method, when the spontaneous breathing effort degree of a patient changes, the method often needs to be adjusted through a plurality of periods, the breathing work of the user can be increased in a longer period, and the breathing cycle burden of the user is increased.

Therefore, a way for improving the man-machine countermeasure problem of the breathing machine in actual clinical use and realizing the man-machine synchronization state more quickly is still lacking at present.

Disclosure of Invention

The invention mainly aims to provide a method, a device, equipment and a storage medium for adjusting a trigger threshold, which can solve the problem of lack of a way for improving man-machine countermeasure of a breathing machine in actual clinical use in the prior art and realize man-machine synchronization state more quickly.

To achieve the above object, a first aspect of the present invention provides a method for adjusting a trigger threshold, the method comprising:

in the process of auxiliary breathing, auxiliary ventilation data of auxiliary breathing equipment and a preset trigger threshold are acquired, wherein the auxiliary ventilation data are used for reflecting the airway state of the auxiliary breathing equipment when the auxiliary breathing equipment performs auxiliary breathing on the basis of triggering of the preset trigger threshold;

performing feature recognition of the human-machine state by using the auxiliary ventilation data, and determining a feature recognition result, wherein the feature recognition result is used for reflecting the human-machine state of the auxiliary breathing equipment;

when the feature recognition result comprises abnormal state features with unsynchronized man-machine states, performing feature quantization processing by using the abnormal state features, and determining an abnormal index of the abnormal state features, wherein the abnormal index is used for reflecting the countermeasure intensity of man-machine countermeasure caused by the abnormal state features;

And adjusting the trigger threshold according to the abnormality index and a preset trigger threshold, determining the adjusted trigger threshold, and returning to execute the step of acquiring the auxiliary ventilation data of the auxiliary respiratory equipment until a shutdown instruction is received, wherein the shutdown instruction is used for controlling the auxiliary respiratory equipment to stop the auxiliary respiratory.

In a possible implementation manner, the adjusting the trigger threshold according to the abnormality index and a preset trigger threshold, and determining the adjusted trigger threshold includes:

determining an adjusting coefficient corresponding to the abnormality index according to a preset corresponding relation between the adjusting coefficient and the abnormality index;

and carrying out compensation adjustment on the trigger threshold by using the adjustment coefficient and a preset trigger threshold, and determining the adjusted trigger threshold.

In a possible implementation manner, the performing feature quantization processing by using the abnormal state feature, and determining an abnormality index of the abnormal state feature includes:

performing abnormality type identification by using the abnormality state characteristics, and determining abnormality types of the abnormality state characteristics, wherein the abnormality types are used for reflecting the asynchronous types of the man-machine state;

And determining an abnormality index of the abnormal state characteristic according to the abnormality type and a preset characteristic quantization algorithm, wherein the quantization algorithm corresponds to the abnormality type one by one.

In a possible implementation manner, the abnormal state feature includes at least an inhalation abnormal feature, and the identifying the abnormal type by using the abnormal state feature, determining the abnormal type of the abnormal state feature includes:

if the abnormal characteristics of the inspiration meet a first condition, determining that the abnormal type of the abnormal characteristics of the inspiration is an inspiration trigger advance, wherein the abnormal characteristics of the inspiration comprise that the auxiliary ventilation equipment is in an inspiration phase and the inspiration flow rate of the inspiration phase is non-monotonic, the first condition is that a first change process exists in the change condition of a first flow rate slope of the inspiration flow rate, and the first change process is that the first flow rate slope is larger than 0, the first flow rate slope is smaller than 0, and the first flow rate slope is smaller than 0;

and if the inhalation abnormal characteristic meets a second condition, determining that the abnormal type of the inhalation abnormal characteristic is an exhalation trigger delay, wherein the inhalation abnormal characteristic comprises that the auxiliary ventilation equipment is in an inhalation phase and a forward overshoot pressure exists at the tail end of a platform pressure of the inhalation phase, and the second condition is that the existence time of the forward overshoot pressure is not lower than a first preset duration threshold.

In a possible implementation manner, the abnormal state feature further includes an abnormal exhalation feature, and the identifying the abnormal type by using the abnormal state feature, determining the abnormal type of the abnormal state feature further includes:

if the abnormal characteristics of the expiration meet a third condition, determining that the abnormal type of the abnormal characteristics of the expiration is an inspiration trigger delay, wherein the abnormal characteristics of the expiration comprise that the auxiliary ventilation equipment is in an expiration phase and the expiration flow rate of the expiration phase is non-monotonic, the third condition is that a second change process exists in the change condition of a second flow rate slope of the expiration phase and zero crossing exists in the second change process, and the second change process is that the second flow rate slope is greater than 0 to the second flow rate slope is less than 0;

if the abnormal expiration characteristic meets a fourth condition, determining that the abnormal type of the abnormal expiration characteristic is expiration triggering advance, wherein the abnormal expiration characteristic comprises that the auxiliary ventilation equipment is in an expiration phase and the expiration flow rate is non-monotonic, the fourth condition is that a third change process exists in the change condition of a third flow rate slope of the expiration phase and is not lower than a second duration threshold, and the third change process is that the third flow rate slope is larger than 0 and the third flow rate slope is smaller than 0.

In a possible implementation manner, the determining, according to the anomaly type and a preset feature quantization algorithm, an anomaly index of the anomaly state feature includes:

when the abnormal type is expiration trigger delay, determining a first abnormality index of the abnormal state feature by using a first platform pressure of an inspiratory phase, a first pressure difference and a preset first quantization algorithm, wherein the first pressure difference is a difference value between forward overshoot pressure and the first platform pressure;

when the abnormal type is the inspiration triggering advance, determining a second abnormal index of the abnormal state characteristic by using a preset second quantization algorithm, a first peak value of the inspiration flow rate of the inspiration phase and a first flow rate difference, wherein the first flow rate difference is a minimum flow rate difference value obtained by iteration when the first flow rate slope of the inspiration phase is smaller than 0;

when the abnormality type is an expiration trigger advance, determining a third abnormality index related parameter of the abnormality state feature by using a first pressure rise amplitude of an expiration phase, a second platform pressure and a first endogenous and preset third quantization algorithm, wherein the first pressure rise amplitude is a difference between a second peak value of iteration of a pressure peak value in a stage that a second flow rate slope of the expiration phase is smaller than 0 and a pressure minimum value in a third change process;

And when the abnormal type is the inspiration trigger delay, determining a fourth abnormality index of the abnormal state characteristic by using a first time difference, a second time difference and a preset fourth quantization algorithm, wherein the first time difference is a time difference between a first time when a second flow rate slope is not lower than a preset slope change threshold value and a first time when airway pressure is not lower than a preset pressure threshold value, and the second time difference is a time difference between a third time when the second flow rate slope starts a second change process and a fourth time when inspiration of a current auxiliary respiratory cycle ends.

In a possible implementation manner, the abnormality type further includes dual triggering of early expiration triggering, and determining an abnormality index of the abnormality status feature according to the abnormality type and a preset feature quantization algorithm further includes:

when the abnormal type is double-trigger of the expiration trigger in advance, determining a fifth abnormal index of the abnormal state characteristic by using a third peak value of expiration flow rate, a flow rate difference value and a preset fifth quantization algorithm, wherein the flow rate difference value is a difference value flow rate of the inspiration end of the current auxiliary breathing cycle and the third peak value;

Determining a sixth abnormality index of the abnormal state feature by using a second endogenous, a second platform pressure and a preset sixth quantization algorithm;

and comprehensively calculating according to the third abnormality index, the fifth abnormality index and the sixth abnormality index, and determining a target abnormality index of the abnormal state feature.

To achieve the above object, a second aspect of the present invention provides an adjustment device for a trigger threshold, the device comprising:

and a data acquisition module: the auxiliary ventilation method comprises the steps that auxiliary ventilation data and a preset trigger threshold value of auxiliary breathing equipment are obtained in the auxiliary breathing process, and the auxiliary ventilation data are used for reflecting the airway state of the auxiliary breathing equipment when the auxiliary breathing equipment triggers auxiliary breathing of a user to be assisted based on the preset trigger threshold value;

and the characteristic recognition module is used for: the auxiliary ventilation data are used for carrying out feature recognition of the human-machine state, and determining a feature recognition result which is used for reflecting the human-machine state of the auxiliary breathing equipment;

and the characteristic quantization module is used for: when the feature recognition result comprises abnormal state features with unsynchronized man-machine states, performing feature quantization processing by using the abnormal state features, and determining an abnormal index of the abnormal state features, wherein the abnormal index is used for reflecting the countermeasure intensity of man-machine countermeasure caused by the abnormal state features;

A threshold adjustment module: and the step of adjusting the trigger threshold according to the abnormality index and a preset trigger threshold, determining the adjusted trigger threshold, and returning to the step of executing the step of acquiring the auxiliary ventilation data of the auxiliary respiratory equipment until a shutdown instruction is received, wherein the shutdown instruction is used for controlling the auxiliary respiratory equipment to stop the auxiliary respiratory.

To achieve the above object, a third aspect of the present invention provides a computer-readable storage medium storing a computer program, which when executed by a processor causes the processor to perform the steps of the method according to the first aspect and any one of the possible implementations.

To achieve the above object, a fourth aspect of the present invention provides a computer device, comprising a memory and a processor, the memory storing a computer program, which when executed by the processor causes the processor to perform the steps of the method according to the first aspect and any one of the possible implementations.

The embodiment of the invention has the following beneficial effects:

the invention provides a method for adjusting a trigger threshold, which comprises the following steps: in the process of auxiliary breathing, auxiliary ventilation data of auxiliary breathing equipment and a preset trigger threshold are acquired, wherein the auxiliary ventilation data are used for reflecting the airway state of the auxiliary breathing equipment when the auxiliary breathing equipment triggers auxiliary breathing of a user to be assisted based on the preset trigger threshold; performing feature recognition of the human-machine state by using the auxiliary ventilation data, and determining a feature recognition result, wherein the feature recognition result is used for reflecting the human-machine state of the auxiliary breathing equipment; when the feature recognition result comprises abnormal state features of which the man-machine states are asynchronous, performing feature quantization processing by using the abnormal state features, and determining an abnormal index of the abnormal state features, wherein the abnormal index is used for reflecting the countermeasure intensity of man-machine countermeasure caused by the abnormal state features; and adjusting the trigger threshold according to the abnormality index and a preset trigger threshold, determining the adjusted trigger threshold, and returning to the step of executing the acquisition of the auxiliary ventilation data of the auxiliary breathing equipment until a shutdown instruction is received, wherein the shutdown instruction is used for controlling the auxiliary breathing equipment to stop auxiliary breathing. According to the method, when the abnormal state characteristics of the asynchronous man-machine state are identified, the abnormal state characteristics are subjected to characteristic quantization processing to evaluate the abnormal indexes of the countermeasure intensity of the man-machine countermeasure, and the preset trigger threshold is adjusted according to the abnormal indexes, so that the adjustment efficiency and accuracy are improved, the man-machine countermeasure problem of the auxiliary breathing equipment is improved, and the man-machine synchronous state can be realized more quickly.

Drawings

In order to more clearly illustrate the embodiments of the invention or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described, it being obvious that the drawings in the following description are only some embodiments of the invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.

Wherein:

FIG. 1 is a flowchart of a method for adjusting trigger threshold according to an embodiment of the present invention;

FIG. 2 is another flow chart of an adjustment of trigger thresholds in accordance with an embodiment of the present invention;

FIG. 3 is a schematic diagram of waveforms of pressure-flow rate during assisted breathing according to an embodiment of the present invention;

FIG. 4 is a second waveform diagram illustrating pressure-flow rate during assisted breathing according to an embodiment of the present invention;

FIG. 5 is a schematic diagram of a waveform of pressure-flow rate during assisted breathing according to an embodiment of the present invention;

FIG. 6 is a schematic diagram of a waveform of pressure-flow rate during assisted breathing according to an embodiment of the present invention;

FIG. 7 is a schematic diagram of waveforms of pressure-flow rate during assisted breathing according to an embodiment of the present invention;

FIG. 8 is a block diagram illustrating a trigger threshold adjustment apparatus according to an embodiment of the present invention;

fig. 9 is a block diagram showing the structure of a computer device according to an embodiment of the present invention.

Detailed Description

The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.

Referring to fig. 1, fig. 1 is a flowchart of a method for adjusting a trigger threshold according to an embodiment of the invention, where the method shown in fig. 1 includes the following steps:

101. in the process of auxiliary breathing, auxiliary ventilation data of auxiliary breathing equipment and a preset trigger threshold are acquired, wherein the auxiliary ventilation data are used for reflecting the airway state of the auxiliary breathing equipment when the auxiliary breathing equipment performs auxiliary breathing on the basis of triggering of the preset trigger threshold;

it will be appreciated that the method shown in the present application may be applied to both a terminal and a server, and that the terminal may specifically be a assisted breathing apparatus or the like. The auxiliary breathing apparatus includes, but is not limited to, an electronic apparatus such as a breathing machine having auxiliary breathing capability, and the server may be implemented as a stand-alone server or a server cluster composed of a plurality of servers. The present embodiment is exemplified as applied to a terminal.

The trigger threshold is used to trigger the assisted breathing apparatus to perform assisted breathing on a user to be assisted (hereinafter referred to as a user), the assisted breathing includes an assisted expiration phase and an assisted inspiration phase, and the trigger threshold includes an inspiration trigger threshold and an expiration trigger threshold. For example, when the airway pressure or airway flow rate reaches an inspiration trigger threshold or an expiration trigger threshold, a corresponding assisted breathing phase may be entered to enable the assisted breathing apparatus to assist the user in taking a respiratory effort. Wherein the secondary respiratory apparatus includes, but is not limited to, a ventilator.

The auxiliary ventilation data includes, but is not limited to, airway pressure, airway flow rate, volume, duration of each respiratory cycle, duration dividing data of different respiratory gas phases, waveform data of flow rate and pressure, waveform data of pressure and flow direction, and the like of the auxiliary respiratory device at any moment, and the waveform data includes pressure, flow rate, volume waveform, peak data and trough data.

For example, when the ventilator is in a high-pressure gas delivery phase (i.e. a gas-sucking phase and a flow velocity forward phase), the flow velocity of the forward flow is reduced due to the exhalation of the user to be assisted, and when the flow velocity of the forward flow or the flow velocity of the forward peak is smaller than or equal to the flow velocity of the gas-sucking triggering threshold, the pressure of the ventilator starts to be reduced, and the user is in a gas discharge phase (i.e. a gas-breathing phase), wherein due to different user states and different gas-supplying pressures, an exact flow velocity threshold is not well defined to measure when the gas is turned, the flow velocity triggering threshold is generally set to be a percentage, and further, in order to prevent the adjustment step length from being too large to oscillate back and forth at a certain triggering threshold, or too small to cause the adjustment speed to be slow, and thus the fixed step length of the flow triggering threshold is 1%; the inspiration trigger threshold refers to a low pressure (during the user's exhaustion phase) of the ventilator, the negative flow rate change is caused by the spontaneous inspiration of the user, when the negative flow rate generated by the inspiration is lower than the inspiration trigger threshold, the pressure of the ventilator starts to rise, and the user is in the inspiration phase (i.e. the inspiration gas phase), wherein, the negative flow rate generated by the inspiration is basically dependent on the effort degree of the inspiration of the user, so that the inspiration trigger threshold can directly use a flow rate threshold, further, in order to prevent the adjustment step from being excessively large to cause subsequent oscillation back and forth at a certain trigger threshold, or excessively small to cause slow adjustment speed, and therefore, the fixed step length of the inspiration trigger threshold takes 0.1LPM (Litre Per Minute) as a minimum single step length.

Further, in the process of assisting breathing, the assisted ventilation data of the assisted breathing equipment and the preset trigger threshold are acquired, the acquisition mode can be to directly read the preset trigger threshold and detect the airway state data of the assisted breathing equipment in real time, so that the assisted ventilation data in the assisted breathing process is obtained, wherein the airway state can be influenced by the autonomous breathing behavior of the user, and the autonomous behavior of the user is monitored.

102. Performing feature recognition of the human-machine state by using the auxiliary ventilation data, and determining a feature recognition result, wherein the feature recognition result is used for reflecting the human-machine state of the auxiliary breathing equipment;

further, after the auxiliary ventilation data are obtained, the man-machine state can be judged, the characteristic recognition of the man-machine state is carried out through the auxiliary ventilation data, the characteristic recognition result is determined, the characteristic recognition result is used for reflecting the man-machine state of the auxiliary breathing equipment, the man-machine state comprises man-machine synchronization and man-machine asynchronism, wherein the man-machine asynchronism means that the breathing cycle of the auxiliary breathing equipment (such as a breathing machine) is not coordinated with a user, and the man-machine asynchronism means that the breathing cycle of the auxiliary breathing equipment (such as the breathing machine) is coordinated with the user. And the feature recognition result at least comprises abnormal state features of the man-machine state synchronization and normal state features of the man-machine state synchronization.

103. When the feature recognition result comprises abnormal state features with unsynchronized man-machine states, performing feature quantization processing by using the abnormal state features, and determining an abnormal index of the abnormal state features, wherein the abnormal index is used for reflecting the countermeasure intensity of man-machine countermeasure caused by the abnormal state features;

it should be noted that, the man-machine state of the current respiratory cycle may be determined according to the feature recognition result, when the feature recognition result includes a feature of man-machine asynchronization, a preset trigger threshold may be adjusted, and when the feature recognition result includes a feature of man-machine asynchronization, the assistance of the respiratory cycle after the current trigger threshold may be continued. Specifically, when the feature recognition result includes an abnormal state feature with an unsynchronized man-machine state, performing feature quantization processing by using the abnormal state feature to determine an abnormal index of the abnormal state feature, wherein the abnormal index is used for reflecting the countermeasure intensity of man-machine countermeasure caused by the abnormal state feature and can also be regarded as a man-machine asynchronous index; and when the feature recognition result comprises normal state features of man-machine state synchronization, returning to the step of acquiring auxiliary ventilation data of the auxiliary breathing equipment until a shutdown instruction is received, wherein the shutdown instruction is used for controlling the auxiliary breathing equipment to stop auxiliary breathing.

The abnormality index is used for reflecting the countermeasure intensity of man-machine countermeasure caused by the abnormal state characteristics of the asynchronous man-machine state, for example, the higher the abnormality index is, the stronger the countermeasure intensity of man-machine countermeasure is, and the lower the abnormality index is, the weaker the countermeasure intensity of man-machine countermeasure is. The abnormal state features include, but are not limited to, abnormal state features including at least an inhalation phase abnormal feature and an exhalation abnormal feature, the inhalation abnormal feature including at least an inhalation trigger advance and an exhalation trigger retard, and the exhalation abnormal feature including at least dual triggers of inhalation trigger retard, exhalation trigger advance, and exhalation trigger advance.

104. And adjusting the trigger threshold according to the abnormality index and a preset trigger threshold, determining the adjusted trigger threshold, and returning to execute the step of acquiring the auxiliary ventilation data of the auxiliary respiratory equipment until a shutdown instruction is received, wherein the shutdown instruction is used for controlling the auxiliary respiratory equipment to stop the auxiliary respiratory.

Further, after the abnormality indexes are obtained, a preset trigger threshold value can be adjusted according to the countermeasure intensity so as to weaken the man-machine countermeasure intensity of man-machine asynchronization, specifically, the trigger threshold value is adjusted according to the abnormality indexes and the preset trigger threshold value, the adjusted trigger threshold value is determined, and when the 'early expiration trigger' or the 'late expiration trigger' occurs, the expiration trigger percentage is correspondingly reduced or increased by using the abnormality indexes; when the 'early inspiration trigger' or the 'late inspiration trigger' occurs, the trigger threshold is correspondingly increased or decreased by using the abnormality index. Or, the product of the coefficients of different sizes and the fixed step size is selected to increase or decrease the trigger threshold according to the size of the man-machine asynchronism index, and the method is not particularly limited in this example, so that the self-adaptive compensation adjustment of inspiration and expiration adapting to individual differences among users is realized, the efficiency of improving man-machine asynchronism is improved, and the speed of man-machine synchronization is improved.

Referring to fig. 2, fig. 2 is another flowchart of a method for adjusting a trigger threshold according to an embodiment of the invention, where the method shown in fig. 2 includes the following steps:

201. in the process of auxiliary breathing, auxiliary ventilation data of auxiliary breathing equipment and a preset trigger threshold are acquired, wherein the auxiliary ventilation data are used for reflecting the airway state of the auxiliary breathing equipment when the auxiliary breathing equipment performs auxiliary breathing on the basis of triggering of the preset trigger threshold;

202. performing feature recognition of the human-machine state by using the auxiliary ventilation data, and determining a feature recognition result, wherein the feature recognition result is used for reflecting the human-machine state of the auxiliary breathing equipment;

203. when the feature recognition result comprises abnormal state features with unsynchronized man-machine states, performing feature quantization processing by using the abnormal state features, and determining an abnormal index of the abnormal state features, wherein the abnormal index is used for reflecting the countermeasure intensity of man-machine countermeasure caused by the abnormal state features;

it should be noted that, the steps 201 to 203 are similar to the steps 101 to 103 shown in fig. 1, and for avoiding repetition, reference may be made to the steps 101 to 103 shown in fig. 1.

In a possible implementation manner, the feature quantization processing using the abnormal state feature determines an abnormality index of the abnormal state feature, and includes steps M10 to M20:

m10, carrying out abnormal type identification by utilizing the abnormal state characteristics, and determining the abnormal type of the abnormal state characteristics, wherein the abnormal type is used for reflecting the asynchronous type of the man-machine state;

m20, determining an abnormality index of the abnormal state feature according to the abnormality type and a preset feature quantization algorithm, wherein the quantization algorithm corresponds to the abnormality type one by one.

It should be noted that, for many reasons that cause man-machine dyssynchrony, for example, the abnormal state features include at least an inhalation phase abnormal feature and an exhalation abnormal feature, and the inhalation abnormal feature includes at least an inhalation trigger advance and an exhalation trigger retard, and the exhalation abnormal feature includes at least a dual trigger of inhalation trigger retard, exhalation trigger advance, and exhalation trigger advance. Therefore, in order to improve the accuracy and efficiency of threshold adjustment, the abnormal indexes of the anomalies of different causes are quantified, specifically, the abnormal state characteristics are utilized to identify the abnormal type, and the abnormal type of the abnormal state characteristics is determined, wherein the abnormal type is used for reflecting the asynchronous type of the man-machine state, and the abnormal type comprises dual triggering of early inspiration triggering, late expiration triggering, late inspiration triggering, early expiration triggering and the like; and determining an abnormality index of the abnormal state characteristics according to the abnormality type and a preset characteristic quantization algorithm, wherein the quantization algorithm corresponds to the abnormality type one by one. And further different abnormality indexes can be obtained by different quantization modes, different abnormality types can be obtained by different abnormality indexes, a quantization algorithm is designed and obtained based on the characteristics of the different abnormality types, and the different abnormality types are converted into numerical expressions through the quantization algorithm so as to carry out subsequent threshold adjustment.

It will be appreciated that the abnormal state features include at least two cases, such as an inhalation abnormal feature and an exhalation abnormal feature, and the inhalation abnormal feature includes at least two cases, such as an inhalation trigger advance and an exhalation trigger retard, and the exhalation abnormal feature includes at least three cases, such as an inhalation trigger retard, an exhalation trigger advance, and a double trigger of an exhalation trigger advance, so that there are at least five abnormal types, and the quantization algorithm is at least five, as will be described in one-to-one manner below.

1) When the abnormal state feature includes an inhalation-phase abnormal feature, the abnormal type may be an exhalation trigger delay, then step M10 may include M11, and step M20 may include M21, specifically:

and M11, if the inhalation abnormal characteristic meets a second condition, determining that the abnormal type of the inhalation abnormal characteristic is an exhalation trigger delay, wherein the inhalation abnormal characteristic comprises that the auxiliary ventilation equipment is in an inhalation phase and forward overshoot pressure exists at the platform pressure end of the inhalation phase, and the second condition is that the existence time of the forward overshoot pressure is not lower than a first preset duration threshold.

And M21, when the abnormal type is expiration trigger delay, determining a first abnormality index of the abnormal state characteristic by using a first platform pressure of an inspiration phase, a first pressure difference and a preset first quantization algorithm, wherein the first pressure difference is a difference value between the forward overshoot pressure and the first platform pressure.

Referring to fig. 3, fig. 3 is a schematic diagram of a waveform of pressure-flow rate during assisted breathing according to an embodiment of the present invention, fig. 3 shows a waveform of pressure-flow rate of a possible delayed expiration trigger, and fig. 3 shows a patient end pressure in cmH2O on an ordinate and a time in s on an abscissa.

When the "delayed expiration trigger" condition occurs, a positive overshoot pressure (shown in fig. 3) typically occurs at the end of the inspiratory plateau pressure, due to the user's voluntary expiration action at this time, but the ventilator fails to recognize the opposition caused by the user's expiration action. Since the gas exhaled by the user increases the pressure in the conduit, resulting in an upward rise in pressure, the difference Δp between the pressure of the overshoot and the plateau pressure can be used as an countermeasure index (syncronyindex) to quantify the phenomenon, defining this characteristic parameter as the first anomaly index SI _InspPress The first quantization algorithm is as in formula (1):

wherein ΔP is the differential pressure between the forward overshoot pressure and the plateau pressure, i.e. the first differential pressure, P _plant For the first plateau pressure, in order to prevent misidentification caused by pressure sampling fluctuation, when the pressure overshoot of the plateau pressure last is longer than the threshold value set in the program (i.e. the existence time of the forward overshoot pressure is not lower than the first preset time period threshold value), the delay phenomenon of expiration triggering is considered to be identified at this time, and M21 is executed to calculate the first abnormality index SI at this time _InspPress Wherein the first preset duration threshold may be set to be not less than 1s or other durations, without limitation, and further executing step 204, the ventilator is further configured to perform according to the characteristic parameter SI _InspPress Is to select different coefficients SI _Param The adjustment of the exhalation trigger threshold is performed by multiplying by a fixed step size (e.g., 1%).

2) Where the abnormal state feature comprises an expiration-related abnormal feature, the abnormal type may be expiration trigger advance, then step M10 may comprise M12, and step M20 may comprise M22, specifically:

m12, if the abnormal expiration characteristic accords with a fourth condition, determining that the abnormal type of the abnormal expiration characteristic is expiration triggering advance, wherein the abnormal expiration characteristic comprises that the auxiliary ventilation equipment is in an expiration phase and the expiration flow rate is non-monotonic, the fourth condition is that a third change process exists in the change condition of a third flow rate slope of the expiration phase and the third change process is not lower than a second duration threshold, and the third change process is that the third flow rate slope is greater than 0 to the third flow rate slope is less than 0;

and M22, when the abnormality type is the expiration trigger advance, determining a third abnormality index of the abnormality state characteristic by using a first pressure rise amplitude of the expiration phase, a second platform pressure and a first endogenous and preset third quantization algorithm, wherein the first pressure rise amplitude is the difference between a second peak value of the iteration of the pressure peak value in a stage that the second flow rate slope of the expiration phase is smaller than 0 and a pressure minimum value during a third change process.

Referring to fig. 4, fig. 4 is a schematic diagram of a pressure-flow rate waveform during assisted breathing according to an embodiment of the present invention, fig. 4 shows a pressure-flow rate waveform of an exhalation trigger advance phenomenon, and fig. 4 shows a patient end pressure in cmH2O on an ordinate and a patient end flow rate in L/min on an abscissa, and a time in s on an abscissa. Δt in fig. 4 refers to the period from the expiration start time to the end of the user's spontaneous inspiration (i.e., the point at which the negative flow rate is again toward the 0 baseline direction). Δt can also be understood as the duration of the change. Wherein waveform 41 is a pressure waveform and waveform 42 is a flow rate waveform.

When the phenomenon of 'expiration triggering advance' occurs, the breathing machine cannot meet the tidal volume required by a user in general, and the breathing machine still keeps the inspiration willingness for a period of time when the pressure of the breathing machine is released. Due to the voluntary inhalation action of the user, a continuous "backflow" phenomenon (as shown in fig. 4) occurs in the flow rate immediately after the expiration phase starts due to the voluntary inhalation of the user, and when the inspiration will be too strong, a second inhalation trigger may occur in a short period after the expiration phase starts (as shown in fig. 5).

Since the patient will normally exhale very poorly at this time, as shown in fig. 4, and pressure is released from the patient at this time, the patient will inhale in advance, and thus will exhibit a "flow rate swing" phenomenon shown by circle 40 in fig. 4 shortly after expiration starts on the flow rate waveform. There are two inflection points in the "flow revolution" point shown for circle 40. The Flow slope change at the inflection points of the two Flow rates has singular points, the identification of the Flow slope singular points is carried out by adopting a least square method, and the linear fitting formula of the Flow rate of the patient is Flow (n) =kn+b, wherein the least square calculation formula of the Flow rate slope can be expressed as formula (2):

where k is the Flow velocity slope of N points in the Flow velocity waveform, flow (N) is the N-point Flow velocity, and N is the number of sampling points between Flow velocity inflection points.

If the flow rate slope follows the change process from "k >0" to "k <0" to "k >0" (i.e., the third change process), and the change process is maintained for a certain time threshold (i.e., the third change process is not lower than the second time period threshold), then the inspiratory flow rate is considered to have a "flow rate slewing" phenomenon. Thus, the identification of the expiration trigger advance phenomenon can be achieved through step M12.

It should be noted that, the second duration threshold refers to that k >0, where k <0 needs to satisfy this phenomenon for a continuous period of time, so as to prevent short-term oscillations of the ventilator signal caused by external interference from being misidentified as occurrence of a "flow velocity swing" phenomenon. Therefore, a time threshold (which may be set as needed, for example, about 10 sampling periods or other times) needs to be set, so that weak man-machine countermeasure is difficult to be identified if the time is too long, and recognition interference caused by other signal noise is easy to be identified by mistake if the time is too short). The time threshold can be matched with the slope threshold to judge, so that the probability of false recognition can be reduced.

Further, the "flow rate slewing" phenomenon in the expiration trigger advance is controlled by the userActive inspiration causes an increase in airway pressure during the pressure release phase, thus defining an airway pressure increase of ΔP _ExpPress Related parameter SI _ExpPress For quantifying the intensity of the patient's challenge, by performing step M22 to obtain an abnormality index SI _ExpPress Wherein, the third quantization algorithm is as formula (3):

in SI _ExpPress For the third abnormality index, ΔP _ExpPress For a first pressure rise amplitude, P _Plant For the second plateau pressure, PEEP is the first endogenous. Wherein DeltaP _ExpPress At k<Carrying out iteration of a pressure peak value in the stage 0, and obtaining a pressure minimum value in the period of 'flow velocity revolution' by subtracting the peak value obtained by iteration; the calculation of endogenous PEEP (Peepi) uses the average of the patient end pressure and end pressure differences over 100ms of end expiration.

It should be noted that, the time threshold of end-expiration 100ms may be changed to a value, and pepi refers to an endogenous pressure formed by the gas in the breathing lung which is not completely exhausted. The value can be preferably 100ms, and the purpose is to prevent the accidental pressure fluctuation at the end of expiration from affecting the calculation result of Peepi, so that the average value of 100ms is taken, the stability of Peepi is ensured, and the step size span is prevented from being larger. The Peepi calculation result of the PEEP, which is the pressure point of the end expiration, is more accurate, but the calculation result of each time can be greatly influenced by noise disturbance, and the time can be shortened and prolonged appropriately according to the actual signal fluctuation condition. The present embodiment is not particularly limited as such.

Moreover, the quantification of (3) is performed mainly in view of whether the pressure provided by the ventilator is large due to the rapid pressure drop. The intensity of negative pressure inhalation challenge by the user at this stage is greater than the intensity of pressure inhalation challenge during stabilization after the pressure drop. Therefore, consider the use of a "flow rate swing" phase, due to the pressure ΔP raised by the user's autonomous negative pressure inhalation _ExpPress As a quantity ofThe user's inspiratory effort is smoothed, not the peak pressure at this stage. Denominator takes platform pressure P _Plant Difference from PEEP.

3) When the abnormal state feature includes an expiration-related abnormal feature, the abnormal type may be expiration trigger advance, then step M10 may include M13, and step M20 may include M23, specifically:

m13, determining that the abnormal type is dual-trigger of expiration trigger advance when expiration abnormal characteristics accord with a fifth condition, wherein the expiration abnormal characteristics are that the auxiliary ventilation equipment is in an expiration phase and the expiration flow rate is non-monotonic, and the fifth condition is that the expiration time interval between two auxiliary ventilation is less than half of the average inspiration time;

m23, when the abnormal type is dual-trigger of the expiration trigger in advance, determining a fifth abnormal index of the abnormal state feature by using a third peak value of expiration flow rate, a flow rate difference value and a preset fifth quantization algorithm, wherein the flow rate difference value is a difference value flow rate between the inspiration flow rate of the inspiration end of the current auxiliary breathing cycle and the third peak value; determining a sixth abnormality index of the abnormal state feature by using a second endogenous, a second platform pressure and a preset sixth quantization algorithm; and comprehensively calculating according to the third abnormality index, the fifth abnormality index and the sixth abnormality index, and determining a target abnormality index of the abnormal state feature.

Referring to fig. 5, fig. 5 is a schematic diagram of a waveform of pressure-flow rate during assisted breathing according to an embodiment of the present invention, fig. 5 shows a waveform of pressure-flow rate of a dual trigger phenomenon of early exhalation trigger, and fig. 5 shows a patient end pressure in cmH2O on the ordinate and a patient end flow rate in L/min on the abscissa, and a time in s on the abscissa.

The "early expiratory trigger" phenomenon in fig. 5 is also called double triggering, and it often happens that the expiratory flow rate cannot return to the baseline normally before the next inspiratory phase arrives, and furthermore, the expiratory time interval between two assisted ventilation is often less than half the mean inspiratory time. So when the above phenomenon is identified by step M13, it is determined that the abnormality type is dual trigger of the exhalation trigger advance.Further, the call end flow parameter correlation index (SI _FlowExp ) Quantifying the expiration triggering advance degree, and obtaining a fifth abnormality index SI through a fifth quantification algorithm shown in the formula (4) _FlowExp Alternatively, the ventilator is used to monitor the correlation index (SI _Peepi ) Quantifying the man-machine asynchronism degree as a characteristic parameter, and obtaining a sixth abnormality index SI through a sixth quantization algorithm shown in (5) _Peepi . I.e. the abnormality index of the phenomenon is determined by step M23.

In SI _FlowExp SI as the fifth abnormality index _Peepi For a sixth abnormality index, PEF is the third peak of the expiratory Flow, Δflow _Exp For the difference flow rate, P, of the end-inspiration flow rate and the peak expiration flow rate PEF _plant Pepi is the second endogenous for the second plateau pressure.

The second endogenous calculation method adopts the average value of the difference value between the end pressure of the patient and the end pressure of the patient within 100 ms. To prevent misrecognition, the early expiratory state identification is performed only within 300ms after the expiration phase begins. After the ventilator recognizes the above phenomenon, step 204 may be executed to determine an abnormality index according to the third abnormality index SI _ExpPress Fifth abnormality index SI _FlowExp And a sixth abnormality index SI _Peepi The different coefficients SIParam are selected to be multiplied by a fixed step size (1%) for adjustment of the exhalation trigger threshold. Or comprehensively calculating according to the third abnormality index, the fifth abnormality index and the sixth abnormality index to determine a target abnormality index of the abnormality state characteristics, and performing step 204 by using the target abnormality index to select different coefficients sipam multiplied by a fixed step length (1%) according to the magnitude of the target abnormality index to adjust the exhalation trigger threshold, wherein the adjustment is not performed And (3) limiting.

Illustratively, the adjustment of the trigger threshold for exhalation: when a plurality of exhalation triggering advance features are identified in a single respiratory cycle and a plurality of feature parameters are calculated, comprehensive calculation processing such as average value calculation is carried out on the corresponding feature parameters, so that the problem of excessive adjustment caused by abnormal feature parameter calculation due to misidentification can be reduced.

Such as: assuming that three expiration trigger advance phenomena are identified within a single cycle, the final characteristic parameter may be expressed as: SIParam= [ (SI) _ExpPress +SI _FlowExp +SI _Peepi )/3.0]；

Or a feature vector confidence (the confidence can represent the reliability of expressing the expiration trigger advance by the feature parameter) can be added later, and then the SIParam is weighted:

SIparam＝[(w1*SI _ExpPress +w2*SI _FlowExp +w3*SI _Peepi )/3.0]

wherein, w1, w2 and w3 are all representing confidence, and w1+w2+w3=1, and the parameter w with high confidence has a larger value. The above is merely exemplary, and is not particularly limited.

4) When the abnormal state feature includes an inspiration-specific abnormal feature, the abnormal type may be an inspiration trigger advance, and then step M10 may include M14, and step M20 may include M24, specifically:

m14, if the abnormal characteristics of the inspiration meet a first condition, determining that the abnormal type of the abnormal characteristics of the inspiration is an inspiration trigger advance, wherein the abnormal characteristics of the inspiration comprise that the auxiliary ventilation equipment is in an inspiration phase and the inspiration flow rate of the inspiration phase is non-monotonic, the first condition is that a first change process exists in the change condition of a first flow rate slope of the inspiration flow rate, and the first change process is that the first flow rate slope is larger than 0 to the first flow rate slope is smaller than 0;

And M24, determining a second abnormality index of the abnormal state characteristic by using a preset second quantization algorithm, a first peak value of the inspiration flow rate of the inspiration phase and a first flow rate difference when the abnormality type is the inspiration trigger advance, wherein the first flow rate difference is a minimum flow rate difference obtained by iteration when the first flow rate slope of the inspiration phase is smaller than 0.

Referring to fig. 6, fig. 6 is a schematic diagram of a waveform of pressure-flow rate during assisted breathing according to an embodiment of the present invention, fig. 6 shows a waveform of pressure-flow rate of an inhalation trigger advancing phenomenon, and fig. 6 shows a patient end pressure in cmH2O on an ordinate and a patient end flow rate in L/min on an abscissa, and a time in s on an abscissa.

It should be noted that, when the ventilation of the ventilator is performed in a "early inhalation trigger" manner, since the patient will usually inhale at this time very weakly, and ventilation is given at this time, the patient may unconsciously support ventilation by the machine by exhaling, and thus, a "flow rate swing" phenomenon may also occur in the flow rate waveform immediately after the start of inhalation, as shown in fig. 6. The method for identifying the phenomenon can also be identified by adopting a slope calculation mode shown in the formula (2), and when the flow rate slope change process (namely the first change process) from 'k > 0' to 'k < 0' occurs after the inhalation phase starts soon, the inhalation triggering advance state is considered to occur. I.e. by performing step M14.

The magnitude of the "turn around flow rate" may vary due to the varying degree of antagonism of the user. To prevent false positive feature points, at k<Iterative obtaining of Flow velocity minimum value delta Flow in stage 0 _Insp Defining characteristic parameters SI _FlowInsp Quantifying the countermeasure intensity, and obtaining the abnormality index SI by executing the quantification algorithm of the step M24 _FlowInsp The quantization algorithm is shown in formula (6):

in SI _FlowInsp As the second abnormality index, Δflow _Insp For the first flow rate difference, PIF is the first peak of the inspiratory flow rate of the inspiratory phase. Since the countermeasure generally occurs shortly after the start of the inspiratory phase, the flow-back condition recognition is performed only within 300ms after the start of the inspiratory phase, when the ventilator recognizesAfter the above phenomenon, the SI is used in step 204 _FlowInsp Adopts the coefficient SIParam with different sizes to multiply by a fixed step (0.1 LPM) to increase the inspiration triggering threshold.

5) Where the abnormal state feature comprises an expiration-related abnormal feature, the abnormal type may be an inspiration trigger delay, then step M10 may comprise M15, and step M20 may comprise M25, specifically:

m15, if the abnormal characteristics of the expiration meet a third condition, determining that the abnormal type of the abnormal characteristics of the expiration is an inspiration trigger delay, wherein the abnormal characteristics of the expiration comprise that the auxiliary ventilation equipment is in an expiration phase and the expiration flow rate of the expiration phase is non-monotonic, the third condition is that a second change process exists in the change condition of a second flow rate slope of the expiration phase and zero crossing exists in the second change process, and the second change process is that the second flow rate slope is greater than 0 to the second flow rate slope is smaller than 0;

And M25, when the abnormal type is the inspiration trigger delay, determining a fourth abnormality index of the abnormal state feature by using a first time difference, a second time difference and a preset fourth quantization algorithm, wherein the first time difference is a time difference between a first time when a second flow rate slope is not lower than a preset slope change threshold value and a first time when airway pressure is not lower than a preset pressure threshold value, and the second time difference is a time difference between a third time when the second flow rate slope starts a second change process and a fourth time when inspiration of a current auxiliary breathing cycle is ended.

Referring to fig. 7, fig. 7 is a schematic diagram of a waveform of pressure-flow rate during assisted breathing according to an embodiment of the present invention, fig. 7 shows a waveform of pressure-flow rate of a possible delayed inhalation trigger, and fig. 7 shows a patient end pressure in cmH2O on an ordinate and a patient end flow rate in L/min on an abscissa, and a time in s on an abscissa.

Fig. 7 shows a "delayed inspiration trigger" phenomenon, which is easily caused by an excessive inspiration trigger threshold or a long pressure rise time. Although the patient's voluntary action of inhalation is ultimately identified as shown in fig. 7, a greater degree of inhalation effort is required for the user to stop. When the patient is not ventilated, continuous inhalation attempts can be made for a long time, and as the differential quantity can be better used for describing the change of the signal, the differential signal characteristic of the flow rate can be used for identifying the inhalation action of the patient. To prevent misrecognition, the identification is started when the flow rate baseline approaches 0 baseline during the expiration phase, and the flow rate differential can be calculated using equation (2) above. If the differential flow rate follows a "k >0" to "k <0" course (i.e., a second course), and the patient flow rate crosses zero during this course, then the ventilator is deemed to have identified a "delay in inspiratory triggering" phenomenon. I.e. the determination of the inspiration trigger delay phenomenon is identified by step M15.

In practice, it is often considered that the user is given effective pressure support when the airway pressure reaches 95% of the set pressure, so that on the basis of the recognition of the "inspiration trigger delay" phenomenon, the recognized flow rate derivative (slope) starts to undergo a large change from the start to the characteristic parameter (SI) related to the time difference Δt between the moment of 95% inspiration pressure _period ) Can be used to quantify the degree of man-machine asynchrony, so the abnormality index SI is calculated by step M25 _period The quantization algorithm can be expressed as formula (7):

in SI _period For the fourth abnormality index, Δt is the first time difference, T _tot Is the second time difference. Wherein T is _tot For the time from the start of the identified slope change in flow rate to the end of the inspiratory phase (i.e., the time difference between the third time the second slope change begins and the fourth time the inspiratory phase of the current assisted breathing cycle ends), the slope change threshold may be a threshold at which a large change in slope change begins, and the preset pressure threshold may be 95% inspiratory pressure. When this is identified, the ventilator may perform step 204 in accordance with SI _period Size selection of (2)The different SIparam times the fixed step size 0.1LPM reduces the inspiration trigger threshold.

204. Determining an adjusting coefficient corresponding to the abnormality index according to a preset corresponding relation between the adjusting coefficient and the abnormality index;

205. Performing compensation adjustment of the trigger threshold by using the adjustment coefficient and a preset trigger threshold, and determining the adjusted trigger threshold; and returning to the step of acquiring the auxiliary ventilation data of the auxiliary respiratory equipment until a shutdown instruction is received, wherein the shutdown instruction is used for controlling the auxiliary respiratory equipment to stop the auxiliary respiratory.

Finally, the triggering threshold value can be adjusted through the obtained abnormality index, so that the accuracy of adjustment is improved, and the interval in which the abnormality index is located is finally judged, the calculated value (all are closed intervals) corresponding to the SIparam, and the final SIparam is determined according to the following rule:

the 3% interval is as follows: siparam=0

3% -10% of the range: siparam=0.5

10% -30% of the range: siparam=1.5

30% -60% of the interval: siparam=3

60% -85% of the range: siparam=5

85% interval up: siparam=8

If only single parameters are relied on, coefficients corresponding to the interval where the SIparam is located are directly taken.

Further, the original preset trigger threshold is adjusted through the coefficient to obtain a new trigger threshold, and an adjusting formula of the trigger threshold is as follows:

expiration trigger advance: new exhalation trigger threshold = previous period exhalation trigger threshold-SIparam 1%;

Delay of expiration triggering: new exhalation trigger threshold = last period exhalation trigger threshold + SIparam 1%;

wherein, the suction trigger adjustment strategy is the same as above, and the formula is expressed as:

inspiration triggering advance: new inspiration trigger threshold = last cycle inspiration trigger threshold + SIparam 0.1;

delay of expiration triggering: new inspiration trigger threshold = last cycle inspiration trigger threshold-SIparam 0.1.

Wherein, the direction of adjustment is opposite to the expiration trigger, the bigger the expiration trigger threshold value, the easier the phase change breathes from the inspiration phase, the bigger the inspiration trigger threshold value, the harder the phase change breathes from the expiration phase. The inhalation phase refers to the inhalation phase of the auxiliary breathing equipment, the breathing machine is in a high-pressure air supply phase at the moment, air is supplied to the lungs of a user, and the flow rate is generally positive at the moment; the expiratory phase refers to the expiratory phase of the auxiliary breathing device, at which the ventilator is in a low pressure phase, the waste gas of the alveoli of the user is discharged, the flow rate is generally negative, and the expiratory phase is generally judged according to the direction of pressure and flow.

The invention provides a method for adjusting a trigger threshold, which comprises the following steps: in the process of auxiliary breathing, auxiliary ventilation data of auxiliary breathing equipment and a preset trigger threshold are acquired, wherein the auxiliary ventilation data are used for reflecting the airway state of the auxiliary breathing equipment when the auxiliary breathing equipment triggers auxiliary breathing of a user to be assisted based on the preset trigger threshold; performing feature recognition of the human-machine state by using the auxiliary ventilation data, and determining a feature recognition result, wherein the feature recognition result is used for reflecting the human-machine state of the auxiliary breathing equipment; when the feature recognition result comprises abnormal state features of which the man-machine states are asynchronous, performing feature quantization processing by using the abnormal state features, and determining an abnormal index of the abnormal state features, wherein the abnormal index is used for reflecting the countermeasure intensity of man-machine countermeasure caused by the abnormal state features; and adjusting the trigger threshold according to the abnormality index and a preset trigger threshold, determining the adjusted trigger threshold, and returning to the step of executing the acquisition of the auxiliary ventilation data of the auxiliary breathing equipment until a shutdown instruction is received, wherein the shutdown instruction is used for controlling the auxiliary breathing equipment to stop auxiliary breathing. In the ventilation process, the man-machine asynchronism degree is analyzed and evaluated through extracting the unsynchronized characteristics of the flow velocity, the pressure and the volume waveforms, and the triggering sensitivity of a patient is automatically adjusted according to different step sizes according to the results (for example, when the 'early triggering of inspiration' is recognized, the breathing machine automatically increases the triggering threshold of inspiration according to the steps by quantifying the recognized characteristic parameters, so that the proper inspiration time of a user is ensured), the man-machine countermeasure problem of the breathing machine in actual clinical use is improved, and the man-machine synchronization state is more rapidly realized. By means of characteristic recognition of triggering relevant delay and advance in the waveforms of flow rate and pressure of the breathing machine and defining several relevant characteristic parameters for quantifying the man-machine asynchronism index, different step sizes are automatically selected according to the man-machine asynchronism degree to adaptively adjust the flow rate triggering threshold value and the expiration triggering percentage, and the man-machine synchronization is responded more rapidly.

Referring to fig. 8, fig. 8 is a block diagram illustrating a trigger threshold adjusting apparatus according to an embodiment of the present invention, where the apparatus shown in fig. 8 includes:

data acquisition module 801: the auxiliary ventilation method comprises the steps that auxiliary ventilation data and a preset trigger threshold value of auxiliary breathing equipment are obtained in the auxiliary breathing process, and the auxiliary ventilation data are used for reflecting the airway state of the auxiliary breathing equipment when the auxiliary breathing equipment triggers auxiliary breathing of a user to be assisted based on the preset trigger threshold value;

feature recognition module 802: the auxiliary ventilation data are used for carrying out feature recognition of the human-machine state, and determining a feature recognition result which is used for reflecting the human-machine state of the auxiliary breathing equipment;

feature quantization module 803: when the feature recognition result comprises abnormal state features with unsynchronized man-machine states, performing feature quantization processing by using the abnormal state features, and determining an abnormal index of the abnormal state features, wherein the abnormal index is used for reflecting the countermeasure intensity of man-machine countermeasure caused by the abnormal state features;

threshold adjustment module 804: and the step of adjusting the trigger threshold according to the abnormality index and a preset trigger threshold, determining the adjusted trigger threshold, and returning to the step of executing the step of acquiring the auxiliary ventilation data of the auxiliary respiratory equipment until a shutdown instruction is received, wherein the shutdown instruction is used for controlling the auxiliary respiratory equipment to stop the auxiliary respiratory.

It should be noted that the functions of each module in the apparatus shown in fig. 8 are similar to those of each step in the method shown in fig. 1, and for avoiding repetition, reference may be made to the contents of each step in the method shown in fig. 1.

The invention provides a trigger threshold adjusting device, which comprises: and a data acquisition module: the auxiliary ventilation method comprises the steps that auxiliary ventilation data of auxiliary breathing equipment and a preset trigger threshold are obtained in the auxiliary breathing process, and the auxiliary ventilation data are used for reflecting the airway state of the auxiliary breathing equipment when the auxiliary breathing equipment triggers auxiliary breathing of a user to be assisted based on the preset trigger threshold; and the characteristic recognition module is used for: the auxiliary ventilation system comprises a breathing assisting device, a breathing assisting device and a breathing assisting device, wherein the breathing assisting device is used for carrying out characteristic recognition of a human-machine state by utilizing auxiliary ventilation data, determining a characteristic recognition result, and reflecting the human-machine state of the breathing assisting device; and the characteristic quantization module is used for: when the feature recognition result comprises abnormal state features of which the man-machine states are asynchronous, performing feature quantization processing by using the abnormal state features, and determining an abnormal index of the abnormal state features, wherein the abnormal index is used for reflecting the countermeasure intensity of man-machine countermeasure caused by the abnormal state features; a threshold adjustment module: and the triggering threshold is adjusted according to the abnormality index and a preset triggering threshold, the adjusted triggering threshold is determined, and the step of acquiring the auxiliary ventilation data of the auxiliary breathing equipment is returned until a stopping instruction is received, wherein the stopping instruction is used for controlling the auxiliary breathing equipment to stop auxiliary breathing. According to the method, when the abnormal state characteristics of the asynchronous man-machine state are identified, the abnormal state characteristics are subjected to characteristic quantization processing to evaluate the abnormal indexes of the countermeasure intensity of the man-machine countermeasure, and the preset trigger threshold is adjusted according to the abnormal indexes, so that the adjustment efficiency and accuracy are improved, the man-machine countermeasure problem of the auxiliary breathing equipment is improved, and the man-machine synchronous state can be realized more quickly.

FIG. 9 illustrates an internal block diagram of a computer device in one embodiment. The computer device may specifically be a terminal or a server. As shown in fig. 9, the computer device includes a processor, a memory, and a network interface connected by a system bus. The memory includes a nonvolatile storage medium and an internal memory. The non-volatile storage medium of the computer device stores an operating system, and may also store a computer program which, when executed by a processor, causes the processor to implement the method described above. The internal memory may also have stored therein a computer program which, when executed by a processor, causes the processor to perform the method described above. It will be appreciated by those skilled in the art that the structure shown in fig. 9 is merely a block diagram of a portion of the structure associated with the present application and is not limiting of the computer device to which the present application applies, and that a particular computer device may include more or fewer components than shown, or may combine some of the components, or have a different arrangement of components.

In one embodiment, a computer device is presented comprising a memory and a processor, the memory storing a computer program that, when executed by the processor, causes the processor to perform the steps of the method as shown in fig. 1 or fig. 2.

In an embodiment, a computer-readable storage medium is proposed, storing a computer program which, when executed by a processor, causes the processor to perform the steps of the method as shown in fig. 1 or fig. 2.

Those skilled in the art will appreciate that all or part of the processes in the methods of the above embodiments may be implemented by a computer program for instructing relevant hardware, where the program may be stored in a non-volatile computer readable storage medium, and where the program, when executed, may include processes in the embodiments of the methods described above. Any reference to memory, storage, database, or other medium used in the various embodiments provided herein may include non-volatile and/or volatile memory. The nonvolatile memory can include Read Only Memory (ROM), programmable ROM (PROM), electrically Programmable ROM (EPROM), electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double Data Rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous Link DRAM (SLDRAM), memory bus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), among others.

The technical features of the above embodiments may be arbitrarily combined, and all possible combinations of the technical features in the above embodiments are not described for brevity of description, however, as long as there is no contradiction between the combinations of the technical features, they should be considered as the scope of the description.

The above examples only represent a few embodiments of the present application, which are described in more detail and are not to be construed as limiting the scope of the present application. It should be noted that it would be apparent to those skilled in the art that various modifications and improvements could be made without departing from the spirit of the present application, which would be within the scope of the present application. Accordingly, the scope of protection of the present application is to be determined by the claims appended hereto.

Claims

1. A method of adjusting a trigger threshold, the method comprising:

2. The method of claim 1, wherein the adjusting the trigger threshold according to the abnormality index and a preset trigger threshold, determining the adjusted trigger threshold, comprises:

3. The method according to claim 1, wherein the performing feature quantization processing using the abnormal state feature, determining an abnormality index of the abnormal state feature, comprises:

4. A method according to claim 3, wherein the abnormal state features include at least an inhalation-induced abnormal feature, and wherein said using the abnormal state features to identify an abnormality type, determining an abnormality type of the abnormal state features, comprises:

5. The method of claim 4, wherein the abnormal state feature further comprises an abnormal exhalation feature, and wherein the using the abnormal state feature to identify the abnormal type, determining the abnormal type of the abnormal state feature further comprises:

6. The method of claim 5, wherein determining the abnormality index for the abnormal state feature according to the abnormality type and a preset feature quantization algorithm comprises:

7. The method of claim 6, wherein the anomaly type further comprises a dual trigger of an early expiratory trigger, and wherein the determining the anomaly index for the anomaly status feature according to the anomaly type and a preset feature quantization algorithm further comprises:

8. An adjustment device for a trigger threshold, the device comprising:

9. A computer readable storage medium storing a computer program, which when executed by a processor causes the processor to perform the steps of the method according to any one of claims 1 to 7.

10. A computer device comprising a memory and a processor, wherein the memory stores a computer program which, when executed by the processor, causes the processor to perform the steps of the method of any of claims 1 to 7.