Ventilator pressure control method and system based on environmental stress and physiological parameters

Abstract

The application provides a ventilator pressure control method and system based on environmental pressure and physiological parameters. The method comprises the following steps: obtaining the environmental atmospheric pressure of a user, a first target output pressure and a physiological parameter; correcting an initial output flow of a ventilator output according to the environmental atmospheric pressure of the user and the first target output pressure to obtain a first output flow; inputting the physiological parameter into a pre-established respiratory pressure deep learning model to obtain a required respiratory pressure of the current physiological parameter, and determining a second output flow required by the ventilator based on the required respiratory pressure of the current physiological parameter; determining an output flow adjustment instruction value required to maintain the stability of the physiological parameter of the user, and controlling the flow output by the ventilator based on the output flow adjustment instruction value. The technical scheme provided by the application can solve the plateau failure problem of the ventilator, enhance the regulation and control effect and the intelligent level, and improve the sleep efficiency.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of respirators, in particular to a respirator pressure control method and system based on environmental pressure and physiological parameters. BACKGROUND

[0002] Plateau refers to an area with an altitude of 3000 meters or above. As the altitude increases, the environmental pressure and oxygen partial pressure gradually decrease. The low-pressure and low-oxygen environment at high altitudes can cause significant damage to various systems of the human body, and the impact on the respiratory system is most obvious. In a sleep environment, due to the lack of active breathing, respiratory compensation is weakened, and unstable ventilation control causes more respiratory events during sleep, among which plateau-related periodic breathing is most common. At this time, a respirator or other equipment is usually needed as an auxiliary means to maintain stable breathing and stable sleep state.

[0003] During the use of the respirator, the patient must be mechanically ventilated. The respirator is equipped with a compressor, a turbine or other types of elements to provide a gas source, and the output flow of the respirator is adjusted to change the output pressure. At the same time, the actual pressure rise pressure decreases with the increase of altitude at the same output flow, so the existing respirator usually has a significant high-altitude failure phenomenon in the plateau environment. At the same time, the human body is more sensitive to changes in physiological indicators in the plateau environment, and a higher precision, individualization and intelligent respirator control method is needed.

[0004] The existing adjustment scheme of the respirator solves the problem of respiratory obstruction of sleep apnea patients during sleep by outputting a specific airflow, and adjusts the working state of the respirator according to whether the user has a respiratory pause event. However, it only adjusts the working state according to the respiratory parameters of the subject, and fails to solve the high-altitude failure problem of the existing respirator and the insufficient fine control, resulting in poor use effect. SUMMARY

[0005] The present application provides a respirator pressure control method and system based on environmental pressure and physiological parameters to at least solve the technical problem of poor use effect caused by the high-altitude failure of the existing respirator and the insufficient fine control.

[0006] The first aspect embodiment of the present application provides a respirator pressure control method based on environmental pressure and physiological parameters, the method comprising:

[0007] obtaining the environmental atmospheric pressure where the user is located, the first target output pressure and the physiological parameters;

[0008] correcting the initial output flow of the respirator according to the environmental atmospheric pressure where the user is located and the first target output pressure to obtain the first output flow;

[0009] inputting the physiological parameter into a pre-established respiratory pressure deep learning model to obtain a required respiratory pressure of the current physiological parameter, and determining a second output flow required by the ventilator based on the required respiratory pressure of the current physiological parameter;

[0010] determining an output flow adjustment instruction value required to maintain stability of the physiological parameter of the user according to the second output flow and the first output flow, and controlling the flow output by the ventilator based on the output flow adjustment instruction value.

[0011] Preferably, the physiological parameter includes heart rate and blood oxygen saturation.

[0012] Further, the initial output flow output by the ventilator is corrected according to the ambient atmospheric pressure where the user is located and the first target output pressure to obtain the first output flow, including:

[0013] determining an initial output flow required by the ventilator under the ambient atmospheric pressure where the user is located, and calculating a pressure value corresponding to the initial output flow;

[0014] determining whether the pressure value corresponding to the initial output flow is equal to the first target output pressure, if yes, taking the initial output flow as the first output flow corresponding to the ventilator under the current environment, otherwise, determining a first difference between the first target output pressure and the pressure value corresponding to the initial output flow, and adjusting the initial output flow based on the first difference until the first difference between the first target output pressure and the pressure value corresponding to the adjusted initial output flow is zero.

[0015] Further, the training process of the respiratory pressure deep learning model includes:

[0016] obtaining heart rate, blood oxygen saturation of each ventilator subject under the ambient atmospheric pressure, and the corresponding ventilator output pressure, and constructing a training set;

[0017] taking the heart rate and blood oxygen saturation of each ventilator subject in the training set as the input of an initial convolutional neural network model, taking the ventilator output pressure in the training set as the output of the initial convolutional neural network model, and optimizing and training the initial convolutional neural network model to obtain a trained respiratory pressure deep learning model.

[0018] Further, the determination of the output flow adjustment instruction value required to maintain the stability of the physiological parameter of the user according to the second output flow and the first output flow, and the control of the flow output by the ventilator based on the output flow adjustment instruction value, include:

[0019] determining a second difference value of the second output flow and the first output flow, and determining a required output flow adjustment instruction value based on the second difference value;

[0020] adjusting the flow output by the breathing machine based on the required output flow adjustment instruction value.

[0021] Further, the method further comprises:

[0022] determining whether the physiological parameters of the user are normal after the adjustment based on the flow adjustment instruction value, and if so, stopping the adjustment, otherwise adjusting the flow output by the breathing machine based on the adjusted physiological parameters of the user.

[0023] The second aspect embodiment of the present application proposes a breathing machine pressure control system based on environmental pressure and physiological parameters, comprising:

[0024] an acquisition module, configured to acquire an environmental atmospheric pressure in which a user is located, a first target output pressure and physiological parameters;

[0025] a first correction module, configured to correct an initial output flow output by a breathing machine according to the environmental atmospheric pressure in which the user is located and the first target output pressure, to obtain a first output flow;

[0026] a determination module, configured to input the physiological parameters into a pre-established breathing pressure deep learning model to obtain a required breathing pressure of a current physiological parameter, and determine a second output flow required by the breathing machine based on the required breathing pressure of the current physiological parameter;

[0027] an adjustment module, configured to determine an output flow adjustment instruction value required to maintain stability of the physiological parameters of the user according to the second output flow and the first output flow, and control the flow output by the breathing machine based on the output flow adjustment instruction value.

[0028] Preferably, the physiological parameters include heart rate and blood oxygen saturation.

[0029] Further, the first correction module comprises:

[0030] a first determination unit, configured to determine an initial output flow required by the breathing machine under the environmental atmospheric pressure in which the user is located, and calculate a pressure value corresponding to the initial output flow;

[0031] The first determining unit is configured to determine whether the pressure value corresponding to the initial output flow is equal to the first target output pressure, and if yes, take the initial output flow as the first output flow corresponding to the breathing machine in the current environment, and if not, determine a first difference between the first target output pressure and the pressure value corresponding to the initial output flow, and adjust the initial output flow based on the first difference until the first difference between the first target output pressure and the pressure value corresponding to the adjusted initial output flow is zero.

[0032] Further, the adjusting module comprises:

[0033] The second determining unit is configured to determine a second difference between the second output flow and the first output flow, and determine a required output flow adjustment instruction value based on the second difference.

[0034] The adjusting unit is configured to adjust the flow output by the breathing machine based on the required output flow adjustment instruction value.

[0035] The embodiments of the present application at least bring the following beneficial effects:

[0036] The present application provides a breathing machine pressure control method and system based on environmental pressure and physiological parameters, wherein the method comprises: obtaining the environmental atmospheric pressure of a user, a first target output pressure and a physiological parameter; correcting an initial output flow output by a breathing machine according to the environmental atmospheric pressure of the user and the first target output pressure to obtain a first output flow; inputting the physiological parameter into a pre-established breathing pressure deep learning model to obtain a required breathing pressure of the current physiological parameter, and determining a required second output flow of the breathing machine based on the required breathing pressure of the current physiological parameter; determining an output flow adjustment instruction value required to maintain the stability of the physiological parameter of the user according to the second output flow and the first output flow, and controlling the flow output by the breathing machine based on the output flow adjustment instruction value. The technical scheme provided by the present application can solve the problem of highland failure of the existing breathing machine equipment, widen the use scenario, enhance the control effect and intelligent level, and improve the sleep efficiency.

[0037] Additional aspects and advantages of the present application will be part of the following description, part will become apparent from the following description, or will be understood by practicing the present application. BRIEF DESCRIPTION OF DRAWINGS

[0038] The above and / or additional aspects and advantages of the present application will become apparent and more readily appreciated from the following description of the embodiments, taken in conjunction with the accompanying drawings, in which:

[0039] Figure 1A flow chart of a ventilator pressure control method based on ambient pressure and physiological parameters according to an embodiment of the present application;

[0040] Figure 2 A flow chart of an ambient pressure compensation algorithm according to an embodiment of the present application;

[0041] Figure 3 A flow chart of a breathing pressure regulation algorithm according to an embodiment of the present application;

[0042] Figure 4 A first structure diagram of a ventilator pressure control system based on ambient pressure and physiological parameters according to an embodiment of the present application;

[0043] Figure 5 A structure diagram of a first correction module according to an embodiment of the present application;

[0044] Figure 6 A second structure diagram of a ventilator pressure control system based on ambient pressure and physiological parameters according to an embodiment of the present application;

[0045] Figure 7 A structure diagram of an adjustment module according to an embodiment of the present application;

[0046] Figure 8 A third structure diagram of a ventilator pressure control system based on ambient pressure and physiological parameters according to an embodiment of the present application. DETAILED DESCRIPTION

[0047] Embodiments of the present application are described in detail below with reference to the attached drawing figures, wherein the same or like reference numerals are used throughout the figures to refer to the same or like elements or elements with the same or similar function. The embodiments described below are exemplary and are intended to be illustrative of the present application and are not to be construed as limiting of the present application.

[0048] The ventilator pressure control method and system based on environmental pressure and physiological parameters provided in the present application, wherein the method comprises: obtaining the environmental atmospheric pressure where the user is located, a first target output pressure and a physiological parameter; correcting the initial output flow of the ventilator output according to the environmental atmospheric pressure where the user is located and the first target output pressure to obtain a first output flow; inputting the physiological parameter into a pre-established respiratory pressure deep learning model to obtain the respiratory pressure required by the current physiological parameter, and determining the second output flow required by the ventilator based on the respiratory pressure required by the current physiological parameter; determining the output flow adjustment instruction value required to maintain the stability of the physiological parameter of the user according to the second output flow and the first output flow, and controlling the flow output by the ventilator based on the output flow adjustment instruction value. The technical solution provided in the present application can solve the plateau failure problem of the existing ventilator equipment, broaden the use scenario, enhance the regulation and control effect and the intelligent level, and improve the sleep efficiency.

[0049] The ventilator pressure control method and system based on environmental pressure and physiological parameters of the embodiments of the present application will be described below with reference to the accompanying drawings.

[0050] Embodiment one

[0051] Figure 1 The flowchart of the ventilator pressure control method based on environmental pressure and physiological parameters provided according to one embodiment of the present application is shown as follows. Figure 1 The method comprises:

[0052] Step 1: obtaining the environmental atmospheric pressure where the user is located, a first target output pressure and a physiological parameter.

[0053] In the embodiments of the present disclosure, the physiological parameter comprises: heart rate, blood oxygen saturation.

[0054] Step 2: correcting the initial output flow of the ventilator output according to the environmental atmospheric pressure where the user is located and the first target output pressure to obtain a first output flow.

[0055] In the embodiments of the present disclosure, the step 2 specifically comprises:

[0056] Step 2-1: determining the initial output flow required by the ventilator under the environmental atmospheric pressure where the user is located, and calculating the pressure value corresponding to the initial output flow.

[0057] It should be noted that the initial output flow required by the ventilator under the environmental atmospheric pressure where the user is located is determined by using the formula , wherein Q eQ0 is the initial output flow required by the breathing machine under the atmospheric pressure of the environment where the user is located, P0 is the first target output pressure under the atmospheric pressure of sea level, and P is the atmospheric pressure of the actual working environment. e Q0 is the initial output flow required by the breathing machine under the atmospheric pressure of the environment where the user is located, P0 is the first target output pressure under the atmospheric pressure of sea level, and P is the atmospheric pressure of the actual working environment.

[0058] Step 2-2: Determine whether the pressure value corresponding to the initial output flow is equal to the first target output pressure. If yes, the initial output flow is taken as the first output flow corresponding to the breathing machine under the current environment. Otherwise, a first difference between the first target output pressure and the pressure value corresponding to the initial output flow is determined, and the initial output flow is adjusted based on the first difference until the first difference between the first target output pressure and the pressure value corresponding to the adjusted initial output flow is zero.

[0059] In the embodiments of the present disclosure, when the actual output pressure is lower than the first target output pressure, the output flow of the breathing machine is increased; when the actual output pressure is higher than the first target output pressure, the output flow of the breathing machine is reduced; until the actual output pressure is equal to the first target output pressure.

[0060] As shown in FIG. 2, the first output flow of the breathing machine is controlled based on the environmental pressure compensation algorithm in the actual execution process, and the specific process is as follows: Figure 2

[0061] Step S201: The user inputs the environmental air pressure and the target output pressure, i.e., the first target output pressure.

[0062] Step S202: The environmental pressure compensation algorithm performs initial output flow calculation.

[0063] In the formula, Q0 is the initial output flow required by the breathing machine under the atmospheric pressure of the environment where the user is located, P0 is the first target output pressure under the atmospheric pressure of sea level, and P is the atmospheric pressure of the actual working environment. determines the initial output flow required by the breathing machine under the atmospheric pressure of the environment where the user is located, wherein Q e Q0 is the initial output flow required by the breathing machine under the atmospheric pressure of the environment where the user is located, P0 is the first target output pressure under the atmospheric pressure of sea level, and P is the atmospheric pressure of the actual working environment. e Q0 is the initial output flow required by the breathing machine under the atmospheric pressure of the environment where the user is located, P0 is the first target output pressure under the atmospheric pressure of sea level, and P is the atmospheric pressure of the actual working environment.

[0064] Step S203: Actual output flow is generated.

[0065] Step S204: Output pressure comparison. According to the generated actual flow, the actual output pressure at this time can be obtained, and the actual output pressure is compared with the first target output pressure. According to the relationship between the actual output pressure and the first target output pressure, it is determined whether the output flow needs to be increased or decreased at this time; ​

[0066] Step S205: The control instruction is transmitted to the ambient pressure compensation algorithm, and the actual output flow is further adjusted until the actual output pressure is equal to the first target output pressure.

[0067] It should be noted that the ambient pressure compensation algorithm aims to eliminate the system error of the ventilator. Since the ventilator calculates the flow as volume flow, the output pressure decreases with the decrease of atmospheric pressure under the same actual output flow. In order to achieve the same pressure increasing effect at high altitude, the formula The ambient pressure compensation is completed.

[0068] Step 3: inputting the physiological parameters into the pre-established respiratory pressure deep learning model to obtain the respiratory pressure required by the current physiological parameters, and determining the second output flow required by the ventilator based on the respiratory pressure required by the current physiological parameters.

[0069] In the embodiments of the present disclosure, the training process of the respiratory pressure deep learning model includes:

[0070] The heart rate, blood oxygen saturation of each ventilator subject under the ambient atmospheric pressure, and the corresponding ventilator output pressure are obtained, and a training set is constructed;

[0071] The heart rate and blood oxygen saturation of each ventilator subject in the training set are used as the input of the initial convolutional neural network model, the ventilator output pressure in the training set is used as the output of the initial convolutional neural network model, the initial convolutional neural network model is optimized and trained, and a trained respiratory pressure deep learning model is obtained.

[0072] Step 4: determining the output flow adjustment instruction value required to maintain the stability of the user's physiological parameters according to the second output flow and the first output flow, and controlling the flow output by the ventilator based on the output flow adjustment instruction value.

[0073] In the embodiments of the present disclosure, the step 4 specifically includes:

[0074] Step 4-1: determining the second difference value of the second output flow and the first output flow, and determining the required output flow adjustment instruction value based on the second difference value;

[0075] Step 4-2: adjusting the flow output by the ventilator based on the required output flow adjustment instruction value.

[0076] As shown in Figure 3 Steps 3 and 4 specifically include:

[0077] Step S301: collecting heart rate information of a user during sleep.

[0078] Step S302: Collect blood oxygen saturation information of the user during sleep.

[0079] Step S303: The closed-loop control algorithm is calculated.

[0080] Step S304: Output pressure matching. The closed-loop control algorithm can find the best target output pressure corresponding to the current blood oxygen saturation and heart rate parameters of the user, i.e. the required respiratory pressure of the current physiological parameters through deep learning means.

[0081] Step S305: The calculated best target output pressure is transmitted to the respirator system.

[0082] Step S306: The respirator system adjusts the output flow according to the required target output pressure, so that the actual output pressure is equal to the best target output pressure.

[0083] Step S307: Implement respiratory control.

[0084] In the embodiments of the present disclosure, the method further comprises:

[0085] determining whether the physiological parameters of the user are normal after adjustment based on the flow adjustment instruction value, if normal, stopping adjustment, otherwise adjusting the flow output by the respirator based on the adjusted physiological parameters of the user.

[0086] In summary, the present embodiment proposes a respirator pressure control method based on environmental pressure and physiological parameters, which compensates for the actual output flow of the respirator according to different environmental pressures, ensures that the actual output flow is equal to the target output flow, and solves the problem of existing respirator failure in high altitude environment; At the same time, according to the physiological parameter characteristics of different individuals, individualized respiratory control is carried out, thereby solving the problems of insufficient intelligent level and relatively extensive control scheme of existing respiratory control method, and improving the control efficiency.

[0087] Embodiment two

[0088] Figure 4 The structure diagram of a respirator pressure control system based on environmental pressure and physiological parameters according to an embodiment of the present application is shown in Figure 4 The system comprises:

[0089] The acquisition module 100 is used to acquire the environmental atmospheric pressure of the user, the first target output pressure and the physiological parameters.

[0090] The physiological parameters include heart rate and blood oxygen saturation.

[0091] The first correction module 200 is used to correct the initial output flow of the ventilator based on the ambient atmospheric pressure of the user's environment and the first target output pressure to obtain the first output flow.

[0092] The determination module 300 is used to input the physiological parameters into a pre-established deep learning model of respiratory pressure to obtain the respiratory pressure required for the current physiological parameters, and to determine the second output flow required by the ventilator based on the respiratory pressure required for the current physiological parameters.

[0093] The adjustment module 400 is used to determine the output flow adjustment command value required to maintain the stability of the user's physiological parameters based on the second output flow and the first output flow, and to control the flow output of the ventilator based on the output flow adjustment command value.

[0094] In the embodiments disclosed herein, such as Figure 5 As shown, the first correction module 200 includes:

[0095] The first determining unit 201 is used to determine the initial output flow rate required by the ventilator under the ambient atmospheric pressure of the user's environment, and to calculate the pressure value corresponding to the initial output flow rate;

[0096] The first judgment unit 202 is used to determine whether the pressure value corresponding to the initial output flow is equal to the first target output pressure. If so, the initial output flow is used as the first output flow of the ventilator in the current environment. Otherwise, the first difference between the first target output pressure and the pressure value corresponding to the initial output flow is determined, and the initial output flow is adjusted based on the first difference until the first difference between the first target output pressure and the pressure value corresponding to the adjusted initial output flow is zero.

[0097] In the embodiments disclosed herein, such as Figure 6 As shown, the system further includes: a training module 500, used for:

[0098] The heart rate, blood oxygen saturation, and corresponding ventilator output pressure of each ventilator subject under the ambient atmospheric pressure were obtained, and a training set was constructed.

[0099] Using the heart rate and blood oxygen saturation of each ventilator subject in the training set as the initial input of the convolutional neural network model, and using the ventilator output pressure in the training set as the initial output of the convolutional neural network model, the initial convolutional neural network model is optimized and trained to obtain a trained deep learning model of respiratory pressure.

[0100] In the embodiments disclosed herein, such as Figure 7 As shown, the adjustment module 400 includes:

[0101] The second determining unit 401 is configured to determine a second difference value of the second output flow and the first output flow, and determine a required output flow adjustment instruction value based on the second difference value.

[0102] The adjusting unit 402 is configured to adjust the flow output by the breathing machine based on the required output flow adjustment instruction value.

[0103] In the embodiments of the present disclosure, as shown in Figure 8 The system further includes a judging module 600, configured to:

[0104] Judge whether the physiological parameter of the user is normal after the adjustment based on the flow adjustment instruction value, and if yes, stop adjusting, and if not, adjust the flow output by the breathing machine based on the adjusted physiological parameter of the user.

[0105] To sum up, the breathing machine pressure control system based on environmental pressure and physiological parameters provided in the embodiments can solve the plateau failure problem of the existing breathing machine and other devices, broaden the use scenarios, reduce the interference of the breathing machine on the sleep process, enhance the control effect and intelligent level, and improve the sleep efficiency.

[0106] In the description of the present specification, the description of the terms "one embodiment", "some embodiments", "an example", "a specific example", or "some examples" and the like means that the specific features, structures, materials or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present application. In the present specification, the illustrative description of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any appropriate manner in any one or more embodiments or examples. In addition, the person skilled in the art can combine and combine the different embodiments or examples described in the present specification and the features of the different embodiments or examples without contradiction.

[0107] Any process or method descriptions in flow charts or described elsewhere herein can be understood as representing one or more steps in a set of steps performed in one or more processes or methods. The scope of preferred embodiments of the present application encompasses numerous additional implementation sequences, examples of which have been provided for the sake of simplicity. The number, arrangement, and interplay of steps can be implemented in various ways with the same or different results. It should be understood that any sequence in the description of processes or methods can be represented in a manner that is different from the presentation.

[0108] Although the embodiments of the present application have been shown and described above, it is understood that the above-described embodiments are exemplary and are not to be construed as limiting the present application, and that changes, modifications, substitutions and variations can be made by those skilled in the art without departing from the scope of the present application.

Claims

1. A method of ventilator pressure control based on environmental pressure and physiological parameters, the method comprising: The method comprises: acquiring the environmental atmospheric pressure where the user is located, a first target output pressure and a physiological parameter; correcting an initial output flow of a breathing machine output according to the environmental atmospheric pressure where the user is located and the first target output pressure to obtain a first output flow; inputting the physiological parameter into a pre-established breathing pressure deep learning model to obtain a breathing pressure required by the current physiological parameter, and determining a second output flow required by the breathing machine based on the breathing pressure required by the current physiological parameter; determining an output flow adjustment instruction value required to maintain the stability of the physiological parameter of the user according to the second output flow and the first output flow, and controlling the flow output by the breathing machine based on the output flow adjustment instruction value.

2. The method of claim 1, wherein, The physiological parameter comprises a heart rate and a blood oxygen saturation.

3. The method of claim 2, wherein, The correcting of the initial output flow of the breathing machine output according to the environmental atmospheric pressure where the user is located and the first target output pressure to obtain the first output flow comprises: determining an initial output flow required by the breathing machine under the environmental atmospheric pressure where the user is located, and calculating a pressure value corresponding to the initial output flow; determining whether the pressure value corresponding to the initial output flow is equal to the first target output pressure, if yes, taking the initial output flow as the first output flow corresponding to the breathing machine under the current environment, otherwise, determining a first difference between the first target output pressure and the pressure value corresponding to the initial output flow, and adjusting the initial output flow based on the first difference until the first difference between the first target output pressure and the pressure value corresponding to the adjusted initial output flow is zero.

4. The method of claim 3, wherein, The training process of the breathing pressure deep learning model comprises: acquiring the heart rate, the blood oxygen saturation and the corresponding breathing machine output pressure of each breathing machine subject under the environmental atmospheric pressure, and constructing a training set; taking the heart rate and the blood oxygen saturation of each breathing machine subject in the training set as the input of an initial convolutional neural network model, taking the breathing machine output pressure in the training set as the output of the initial convolutional neural network model, and optimizing and training the initial convolutional neural network model to obtain a trained breathing pressure deep learning model.

5. The method of claim 3, wherein, The determining of the output flow adjustment instruction value required to maintain the stability of the physiological parameter of the user according to the second output flow and the first output flow, and the controlling of the flow output by the breathing machine based on the output flow adjustment instruction value comprise: determining a second difference between the second output flow and the first output flow, and determining the required output flow adjustment instruction value based on the second difference; adjusting the flow output by the breathing machine based on the required output flow adjustment instruction value.

6. The method of claim 5, wherein, The method further comprises: determining whether the physiological parameter of the user is normal after the adjustment based on the flow adjustment instruction value, if yes, stopping the adjustment, otherwise, adjusting the flow output by the breathing machine based on the adjusted physiological parameter of the user.

7. A ventilator pressure control system based on environmental pressure and physiological parameters, characterized by, The system comprises: an acquisition module configured to acquire the environmental atmospheric pressure where the user is located, a first target output pressure and a physiological parameter; The first correction module is configured to correct an initial output flow of the breathing machine according to an atmospheric pressure of an environment where the user is located and the first target output pressure, to obtain a first output flow; The determination module is configured to input the physiological parameter into a pre-established breathing pressure deep learning model to obtain a required breathing pressure of the current physiological parameter, and determine a second output flow required by the breathing machine based on the required breathing pressure of the current physiological parameter. The adjustment module is configured to determine an output flow adjustment instruction value required to maintain stability of the physiological parameter of the user according to the second output flow and the first output flow, and control the flow output by the breathing machine based on the output flow adjustment instruction value.

8. The system of claim 7, wherein, The physiological parameter includes a heart rate and a blood oxygen saturation.

9. The system of claim 8, wherein, The first correction module includes: A first determination unit is configured to determine an initial output flow required by the breathing machine under the atmospheric pressure of the environment where the user is located, and calculate a pressure value corresponding to the initial output flow; A first judgment unit is configured to determine whether the pressure value corresponding to the initial output flow is equal to the first target output pressure, if yes, the initial output flow is taken as the first output flow corresponding to the breathing machine under the current environment, otherwise, a first difference between the first target output pressure and the pressure value corresponding to the initial output flow is determined, and the initial output flow is adjusted based on the first difference until the first difference between the first target output pressure and the pressure value corresponding to the adjusted initial output flow is zero.

10. The system of claim 9, wherein, The adjustment module includes: A second determination unit is configured to determine a second difference between the second output flow and the first output flow, and determine a required output flow adjustment instruction value based on the second difference; An adjustment unit is configured to adjust the flow output by the breathing machine based on the required output flow adjustment instruction value.

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