A respiratory monitoring method and ventilator based on big data analysis

Abstract

The present application discloses a respiratory monitoring method and a ventilator based on big data analysis, which relate to the technical field of medical equipment; by determining a target respiratory index that characterizes the respiratory stability of the ventilator user and a target respiratory symptom type that characterizes the respiratory symptoms of the ventilator user; combining the target respiratory index, the target respiratory symptom type and the preset parameter library, the target oxygen parameter is determined to control the ventilator according to the target oxygen parameter. This control method of the ventilator, combined with the relevant monitoring data of the ventilator user, realizes automatic oxygen control of the ventilator, which is equivalent to realizing automatic oxygen control of the ventilator on the basis of respiratory monitoring, so that the oxygen parameters of the ventilator can accurately meet the needs of the ventilator user. Thereby, effective and timely respiratory monitoring is achieved, thereby ensuring the application stability of the ventilator and improving the user experience of the ventilator user.

Description

Technical Field

[0001] The present application relates to the field of medical equipment technology, and in particular to a respiratory monitoring method and a ventilator based on big data analysis. Background Art

[0002] With the development of medical equipment technology, the application of ventilators is becoming more and more widespread. In some medical scenarios, ventilators can be used to assist patients in breathing to solve the problem of patients' breathing difficulties. During the use of ventilators, since the patient's condition may change at any time, it is usually necessary to monitor the patient's real-time condition in order to control the ventilator accordingly so that the application of the ventilator can meet the patient's needs.

[0003] In the related art, the patient's condition is usually observed manually, and the parameters of the ventilator are adjusted according to the observation results. This method cannot achieve effective and timely respiratory monitoring, and thus cannot ensure the application stability of the ventilator. Summary of the invention

[0004] The purpose of this application is to provide a respiratory monitoring method and a ventilator based on big data analysis, so as to achieve effective and timely respiratory monitoring, thereby ensuring the application stability of the ventilator and improving the user experience of the ventilator.

[0005] To achieve the above-mentioned objectives, in a first aspect, an embodiment of the present application provides a respiratory monitoring method based on big data analysis, including: obtaining physiological parameter monitoring data and diagnostic data of a ventilator user; determining a target respiratory index based on the physiological parameter monitoring data, wherein the target respiratory index is used to characterize the respiratory stability of the ventilator user; determining a target respiratory symptom type based on the diagnostic data, wherein the target respiratory symptom type is used to characterize the respiratory symptoms of the ventilator user; determining a target oxygen parameter based on the target respiratory index, the target respiratory symptom type and a preset parameter library, wherein the preset parameter library includes: a correspondence between preset respiratory symptom types, preset respiratory indices and preset oxygen parameters; and controlling the ventilator based on the target oxygen parameter.

[0006] In a possible implementation, the oxygen parameter includes oxygen flow, and the respiratory monitoring method further includes: obtaining operating information of the ventilator, the operating information including a current operating mode and an operating duration of the current operating mode, different operating modes corresponding to different oxygen flow thresholds; correspondingly, obtaining physiological parameter monitoring data and diagnostic data of the ventilator user includes: if the operating duration of the current operating mode is greater than the preset operating duration, or the operating duration of the current operating mode is less than or equal to the preset operating duration, and the difference between the oxygen flow threshold corresponding to the current operating mode and the oxygen flow threshold corresponding to the previous operating mode is greater than the preset difference, obtaining the physiological parameter monitoring data and diagnostic data of the ventilator user.

[0007] In a possible implementation, the physiological parameter monitoring data includes: blood oxygen data, pulse rate data, blood pressure data, carbon dioxide data, oxygen concentration data and respiratory rate data, and determining the target respiratory index based on the physiological parameter monitoring data includes: determining a first respiratory index based on the blood oxygen data, the pulse rate data, the oxygen concentration data and the respiratory rate data; determining a second respiratory index based on the carbon dioxide data and the oxygen concentration data; determining a third respiratory index based on the blood pressure data and the pulse rate data; and determining a target respiratory index based on the first respiratory index, the second respiratory index and the third respiratory index.

[0008] In a possible implementation, determining the target breathing index according to the first breathing index, the second breathing index and the third breathing index includes: comparing the first breathing index with a preset breathing index range to obtain a comparison result; if the first breathing index is within the preset breathing index range, determining a breathing index adjustment value according to the second breathing index, the weight corresponding to the second breathing index and the third breathing index; if the first breathing index is not within the preset breathing index range, determining a breathing index adjustment value according to the second breathing index, the weight corresponding to the second breathing index, the third breathing index and the weight corresponding to the third breathing index, wherein the weight corresponding to the second breathing index is less than the weight corresponding to the third breathing index; determining the target breathing index according to the first breathing index and the breathing index adjustment value.

[0009] In a possible implementation, determining the target breathing index based on the first breathing index, the second breathing index and the third breathing index includes: obtaining the first breathing index corresponding to multiple historical time points respectively; determining the first breathing index change rate according to the first breathing index corresponding to the multiple historical time points and the first breathing index; if the first breathing index change rate is greater than or equal to a preset breathing index change rate, determining the first breathing index as the target breathing index; if the first breathing index change rate is less than the preset breathing index change rate, determining the breathing index adjustment value according to the second breathing index, the weight corresponding to the second breathing index, the third breathing index and the weight corresponding to the third breathing index, wherein the weight corresponding to the second breathing index is less than the weight corresponding to the third breathing index; determining the target breathing index according to the first breathing index and the breathing index adjustment value.

[0010] In a possible implementation, determining the target respiratory symptom type based on the diagnostic data includes: extracting key diagnostic information corresponding to multiple dimensions from the diagnostic data, the multiple dimensions including: a doctor's opinion dimension, a patient description information dimension, and a patient's actual measured data dimension; inputting the key diagnostic information corresponding to the multiple dimensions into a pre-trained prediction model to obtain prediction information output by the pre-trained prediction model, the prediction information including: spontaneous breathing level and assisted breathing level, different spontaneous breathing levels corresponding to different spontaneous breathing abilities, and different assisted breathing levels corresponding to different assisted breathing intensities; determining the target respiratory symptom type based on the spontaneous breathing level and the assisted breathing level.

[0011] In a possible implementation, the respiratory monitoring method further includes: in response to detecting a query request from a medical staff, determining a parameter adjustment item from a preset parameter adjustment library according to the query request, wherein the query request includes monitoring data recorded by the medical staff for a ventilator user, and the preset parameter adjustment library includes: a correspondence between preset monitoring data and preset parameter adjustment items; feeding back the parameter adjustment items; correspondingly, controlling the ventilator according to the target oxygen parameter includes: obtaining a parameter adjustment instruction input by the medical staff based on the parameter adjustment item; obtaining a current oxygen parameter of the ventilator; determining, according to the current oxygen parameter, the target oxygen parameter and the parameter adjustment instruction, an oxygen parameter to be adjusted and a parameter adjustment value corresponding to the oxygen parameter to be adjusted; and controlling the ventilator according to the oxygen parameter to be adjusted and the parameter adjustment value corresponding to the oxygen parameter to be adjusted.

[0012] In a possible implementation, the respiratory monitoring method further includes: acquiring oxygen source monitoring data, the oxygen source monitoring data including oxygen source masses corresponding to a plurality of monitoring time points; determining an oxygen source quality monitoring result according to the oxygen source masses corresponding to the plurality of monitoring time points, the oxygen source quality monitoring result being used to characterize whether the oxygen source quality is abnormal; correspondingly, controlling the ventilator according to the target oxygen parameter includes: if the oxygen source quality monitoring result characterizes that the oxygen source quality is abnormal, feeding back prompt information, the prompt information being used to indicate optimization of the oxygen source quality; in response to receiving external input information characterizing completion of oxygen source quality optimization, controlling the ventilator according to the target oxygen parameter.

[0013] In a possible implementation, controlling the ventilator according to the target oxygen parameter includes: acquiring a current oxygen parameter of the ventilator; determining an oxygen parameter to be adjusted and a parameter adjustment value corresponding to the oxygen parameter to be adjusted according to the current oxygen parameter and the target oxygen parameter; if the number of the oxygen parameters to be adjusted is less than a preset number, and / or the parameter adjustment value corresponding to the oxygen parameter to be adjusted is less than a preset parameter adjustment value, acquiring noise monitoring data, the noise monitoring data including noise monitoring values ​​corresponding to a plurality of monitoring time points; determining a denoising strategy according to the noise monitoring data, the denoising strategy being associated with an oxygen parameter adjustment method and / or a heating method of an oxygen heating pipeline of the ventilator; and controlling the ventilator according to the oxygen parameter to be adjusted, the parameter adjustment value corresponding to the oxygen parameter to be adjusted, and the denoising strategy.

[0014] In a second aspect, an embodiment of the present application provides a ventilator, comprising: a physiological parameter monitoring device for monitoring the physiological parameters of a ventilator user; an oxygen source monitoring device for monitoring the quality of the oxygen source; a noise monitoring device for monitoring noise; a display device; and a control device, which is respectively connected to the physiological parameter monitoring device, the oxygen source monitoring device, the noise monitoring device and the display device, and is used to execute the respiratory monitoring method based on big data analysis as described in the first aspect.

[0015] Compared with the prior art, the technical solution provided by this application has the following technical effects:

[0016] Through the physiological parameter monitoring data of the ventilator user, the target respiratory index that characterizes the respiratory stability of the ventilator user is determined, and through the diagnostic data of the ventilator user, the target respiratory symptom type that characterizes the respiratory symptoms of the ventilator user is determined; then, the target respiratory index, the target respiratory symptom type and the preset parameter library are combined to determine the target oxygen parameter, so as to control the ventilator according to the target oxygen parameter. Through this control method of the ventilator, the automatic oxygen control of the ventilator can be realized in combination with the relevant monitoring data of the ventilator user, which is equivalent to realizing the automatic oxygen control of the ventilator on the basis of respiratory monitoring, so that the oxygen parameters of the ventilator can accurately meet the needs of the ventilator user. Therefore, this technical solution can realize effective and timely respiratory monitoring, thereby ensuring the application stability of the ventilator and improving the user experience of the ventilator user. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 is a schematic diagram of the external structure of a ventilator according to an embodiment of the present application;

[0018] Figure 2 is a structural block diagram of a ventilator according to an embodiment of the present application;

[0019] Figure 3 is a flow chart of a respiratory monitoring method based on big data analysis according to an embodiment of the present application;

[0020] Figure 4 It is a schematic diagram of the structure of a control device according to an embodiment of the present application. DETAILED DESCRIPTION

[0021] The specific implementation methods of the present application are described in detail below in conjunction with the accompanying drawings, but it should be understood that the protection scope of the present application is not limited by the specific implementation methods.

[0022] Unless explicitly stated otherwise, throughout the specification and claims, the term “comprise” or variations such as “include” or “comprising”, etc., will be understood to include the stated elements or components but not to exclude other elements or components.

[0023] With the development of medical equipment technology, the application of ventilators is becoming more and more widespread. In some medical scenarios, ventilators can be used to assist patients in breathing to solve the problem of patients' breathing difficulties. During the use of ventilators, since the patient's condition may change at any time, it is usually necessary to monitor the patient's real-time condition in order to control the ventilator accordingly so that the application of the ventilator can meet the patient's needs.

[0024] In the related art, the patient's condition is usually observed manually, and the parameters of the ventilator are adjusted according to the observation results. This method cannot achieve effective and timely respiratory monitoring, and thus cannot ensure the application stability of the ventilator.

[0025] Based on this, the embodiment of the present application provides a technical solution, which combines the relevant monitoring data of the ventilator user to realize the automatic oxygen control of the ventilator, which is equivalent to realizing the automatic oxygen control of the ventilator on the basis of respiratory monitoring, so that the oxygen parameters of the ventilator can accurately meet the needs of the ventilator user. Thus, effective and timely respiratory monitoring is achieved, thereby ensuring the application stability of the ventilator and improving the user experience of the ventilator user.

[0026] The technical solution provided in the embodiment of the present application can be applied to various application scenarios involving ventilators. In some application scenarios, the role of the ventilator may be to assist the patient in breathing. In other application scenarios, the performance of the ventilator may be studied, so its role may be as an experimental device.

[0027] Please refer to Figure 1 , is a schematic diagram of the appearance structure of a ventilator according to an embodiment of the present application, such as Figure 1 As shown, the ventilator has a corresponding operating console and corresponding pipelines, the ends of which are connected to corresponding ventilator users, and oxygen can be delivered through the corresponding pipelines.

[0028] Regarding the basic principles of ventilators, you can refer to the mature technology in this field and will not introduce them in detail here.

[0029] Please refer to Figure 2 , is a structural block diagram of a ventilator according to an embodiment of the present application, the ventilator includes: a control device, a physiological parameter monitoring device, an oxygen source monitoring device, a noise monitoring device and a display device.

[0030] The control device is connected to the physiological parameter monitoring device, the oxygen source monitoring device, the noise monitoring device and the display device respectively, and the connection here can be an electrical connection or a communication connection.

[0031] Regarding the physiological parameter monitoring device, it can be used to monitor the physiological parameters of the ventilator user, and the physiological parameters may include: blood oxygen, pulse rate, blood pressure, carbon dioxide, oxygen concentration and respiratory rate, etc.

[0032] The physiological parameter monitoring device may include multiple sub-monitoring devices, and different sub-monitoring devices are used to monitor different physiological parameters. These multiple sub-monitoring devices may be monitoring devices configured on the ventilator or external monitoring devices, which can transmit data to the control device or the corresponding data integration module.

[0033] For example, blood oxygen, pulse rate and respiratory rate can be monitored through some smart wearable devices. Blood pressure can be monitored through a blood pressure monitor. Carbon dioxide can be monitored through a gas sensor. Oxygen concentration can also be monitored through a gas sensor, or calculated by a ventilator based on its oxygen parameters.

[0034] The oxygen source monitoring device is used to monitor the quality of the oxygen source, and it can be installed on the oxygen source. The quality of the oxygen source can be reflected by some corresponding parameters, such as oxygen concentration and oxygen purity. The implementation of the oxygen source monitoring device can be implemented with reference to some mature gas quality measurement devices in the field, which will not be introduced in detail here. For example, at every preset period, some oxygen is extracted from the oxygen source, and then the gas ratio therein is calculated to determine the oxygen concentration and oxygen purity, and then the oxygen concentration and oxygen purity are integrated to determine the quality of the oxygen source.

[0035] The noise monitoring device is used to monitor noise. It can be installed on the ventilator body or near the ventilator, for example, under the bed where the ventilator user lies. The device can be a noise sensor or the like, which can realize noise detection.

[0036] Regarding the display device, it can be installed on the ventilator body or a separate part, which can be a touch screen or a non-touch screen. The display device can also be configured with corresponding input and output modules, such as a keyboard, a mouse, and a stylus. The size of the display device can be large to facilitate human-computer interaction.

[0037] The control device may be a controller, and the controller may be various types of controllers, such as a microcontroller, etc. The control device is integrated inside the ventilator body to play a corresponding protective role.

[0038] It is understood that the ventilator may include more modules capable of realizing basic functions in addition to the above modules. Figure 1 and Figure 2 For example, the ventilator may also include: a memory card, a communication module (wireless communication and / or wired communication), a network interface, a built-in lithium battery, a water box, a water level detection device of the water box, and a high and low pressure oxygen interface.

[0039] The high and low pressure oxygen interfaces can be used to switch the working mode of the ventilator, that is, when different interfaces are used, the oxygen parameters of the ventilator are different.

[0040] Please refer to Figure 3 , is a flow chart of a respiratory monitoring method based on big data analysis according to an embodiment of the present application, the respiratory monitoring method comprising the following steps:

[0041] Step 301, obtaining physiological parameter monitoring data and diagnostic data of a ventilator user.

[0042] Step 303: Determine a target breathing index according to the physiological parameter monitoring data. The target breathing index is used to characterize the breathing stability of the ventilator user.

[0043] Step 303: Determine a target respiratory symptom type according to the diagnostic data. The target respiratory symptom type is used to characterize the respiratory symptoms of the ventilator user.

[0044] Step 304, determining a target oxygen parameter according to the target respiratory index, the target respiratory symptom type and a preset parameter library, wherein the preset parameter library includes a correspondence between preset respiratory symptom types, preset respiratory indices and preset oxygen parameters.

[0045] Step 305, controlling the ventilator according to the target oxygen parameter.

[0046] In the embodiment of the present application, the ventilator user can be understood as a user who is currently using the ventilator.

[0047] Regarding the physiological parameter monitoring data of the ventilator user, refer to the above-mentioned embodiment, which can be obtained from the corresponding monitoring device.

[0048] The diagnostic data about the ventilator user may be the diagnostic data uploaded by medical staff.

[0049] In some embodiments, the ventilator can be connected to a related server of the hospital system through a network interface, so that the ventilator can also obtain the diagnostic data of the ventilator user from the related server.

[0050] In some embodiments, steps 301 to 305 may be performed periodically to achieve continuous respiratory monitoring.

[0051] In other embodiments, respiratory monitoring may be performed under corresponding conditions. Therefore, as an optional implementation, before step 301, the method further includes: obtaining operating information of the ventilator, the operating information including the current operating mode and the operating time of the current operating mode, and different operating modes correspond to different oxygen flow thresholds.

[0052] In an embodiment of the present application, the ventilator can be set to at least two operating modes, for example, a high flow mode and a normal flow mode. When in high flow mode, the oxygen flow threshold is high and the oxygen delivery amount is also large. When in normal flow mode, the oxygen flow threshold is not very high and the oxygen delivery amount is not very large. Therefore, the oxygen flow threshold of the high flow mode is greater than the oxygen flow threshold of the normal flow mode.

[0053] Among them, oxygen flow rate can be used as an oxygen parameter. In addition to oxygen flow rate, oxygen parameters can also include: oxygen flow rate, oxygen delivery speed and oxygen temperature, etc. Among them, oxygen flow rate can be controlled by switching the oxygen delivery pipeline. For example, the oxygen flow rate corresponding to the delivery pipeline with a large diameter is higher than the oxygen flow rate corresponding to the delivery pipeline with a small diameter. The oxygen delivery speed can be controlled by the valve opening of the delivery pipeline. For example, the larger the valve opening, the faster the oxygen delivery speed. The oxygen temperature can be controlled by controlling the heating method of the heating pipeline. For example, the greater the heating intensity, the higher the oxygen temperature.

[0054] In actual applications, the oxygen flow threshold corresponding to the high flow mode or the normal flow mode can be configured according to specific scenarios, and the value is not limited here.

[0055] The running time of the current running mode is the running information of the ventilator and can be directly obtained.

[0056] Accordingly, the operating time of the current operating mode and the preset operating time can be compared, and the difference between the oxygen flow threshold corresponding to the current operating mode and the oxygen flow threshold corresponding to the previous operating mode can be determined.

[0057] Thus, step 301 may include: if the operating time of the current operating mode is greater than the preset operating time, or the operating time of the current operating mode is less than or equal to the preset operating time, and the difference between the oxygen flow threshold corresponding to the current operating mode and the oxygen flow threshold corresponding to the previous operating mode is greater than the preset difference, obtaining the physiological parameter monitoring data and diagnostic data of the ventilator user.

[0058] In this implementation, if the running time of the current running mode is greater than the preset running time, it means that the current running mode has been running for a long time and respiratory monitoring is required.

[0059] If the running time of the current running mode is less than or equal to the preset running time, it means that the current running mode is a mode that has just been switched. Therefore, it is necessary to further determine whether the difference between the oxygen flow threshold corresponding to the current running mode and the oxygen flow threshold corresponding to the previous running mode is greater than the preset difference. If so, it means that the oxygen flow changes rapidly and respiratory monitoring is required. Otherwise, respiratory monitoring is not required for the time being.

[0060] The preset operation time may be the time required for the ventilator to operate stably after the mode is switched, such as 10 minutes, 15 minutes, or 20 minutes. The preset difference may be a value representing a large oxygen flow difference, such as the difference between the oxygen flow threshold of the high flow mode and the oxygen flow threshold of the normal flow mode.

[0061] In step 302, a target breathing index is used to characterize the breathing stability of a ventilator user.

[0062] In some embodiments, the target respiratory index can be a ROX index. The ROX index is the ratio of oxygen saturation divided by the inspired oxygen concentration to the respiratory rate. As one of the early predictive indicators for judging the success of high-flow oxygen inhalation, the ROX index can guide when to perform endotracheal intubation during high-flow oxygen inhalation to prevent treatment delays and appropriately allocate resources. The ROX index can also be used to identify high-risk patients who require intubation during high-flow oxygen inhalation, which may help guide intubation decisions.

[0063] In addition, there are related parameters such as ROX-HR index, mROX index and mROX-HR index, which are calculated by different formulas and used to more comprehensively evaluate the patient's respiratory condition.

[0064] Therefore, on the basis that the target index is the ROX index, the ROX index can be determined according to the blood oxygen data, pulse rate data, oxygen concentration data and respiratory rate data.

[0065] The blood oxygen data may include blood oxygen saturation, which can be used as oxygen saturation, oxygen concentration and respiratory rate to calculate the ROX index.

[0066] In other embodiments, the target respiratory index may be a respiratory index determined based on the aforementioned ROX index and more customized indexes.

[0067] Therefore, as an optional implementation, the physiological parameter monitoring data includes: blood oxygen data, pulse rate data, blood pressure data, carbon dioxide data, oxygen concentration data and respiratory rate data. Step 302 includes: determining a first respiratory index according to the blood oxygen data, pulse rate data, oxygen concentration data and respiratory rate data; determining a second respiratory index according to the carbon dioxide data and the oxygen concentration data; determining a third respiratory index according to the blood pressure data and the pulse rate data; and determining a target respiratory index according to the first respiratory index, the second respiratory index and the third respiratory index.

[0068] The implementation of the first respiratory index may refer to the implementation of the aforementioned ROX index. Regarding the second respiratory index, the carbon dioxide data may be the carbon dioxide concentration, and the second respiratory index may be the ratio of the carbon dioxide concentration to the oxygen absorption concentration. Regarding the third respiratory index, the blood pressure data may be the blood pressure value, and the third respiratory index may be the ratio of the blood pressure value to the pulse rate.

[0069] In some embodiments, the second respiratory index may represent the relationship between carbon dioxide concentration and oxygen absorption concentration, and the third respiratory index may represent the relationship between blood pressure value and pulse rate.

[0070] As a first optional implementation, a target breathing index is determined according to a first breathing index, a second breathing index and a third breathing index, including: comparing the first breathing index with a preset breathing index range to obtain a comparison result; if the first breathing index is within the preset breathing index range, determining a breathing index adjustment value according to the second breathing index, the weight corresponding to the second breathing index and the third breathing index; if the first breathing index is not within the preset breathing index range, determining the breathing index adjustment value according to the second breathing index, the weight corresponding to the second breathing index, the third breathing index and the weight corresponding to the third breathing index, wherein the weight corresponding to the second breathing index is less than the weight corresponding to the third breathing index; determining the target breathing index according to the first breathing index and the breathing index adjustment value.

[0071] In this embodiment, the preset breathing index range may be a breathing index range that characterizes a normal breathing condition, and may be specifically configured according to different application scenarios, and the value is not limited here.

[0072] If the first respiratory index is within the preset respiratory index range, it means that judging from the first respiratory index, there is no problem with the respiratory stability. Therefore, at this time, the respiratory index adjustment value can be determined based on the second respiratory index and the third respiratory index, and the respiratory index adjustment value can adjust the first respiratory index.

[0073] In some embodiments, the effect of the second respiratory index on respiratory stability is less than the effect of the third respiratory index on respiratory stability. Therefore, in this case, the second respiratory index can be multiplied by the weight corresponding to the second respiratory index, and then added to the third respiratory index to determine the respiratory index adjustment value. The weight corresponding to the second respiratory index is less than 1.

[0074] If the first respiratory index is not within the preset respiratory index range, it means that judging from the first respiratory index, there is a problem with the respiratory stability. At this time, a respiratory index adjustment value can also be determined based on the second respiratory index and the third respiratory index, and the respiratory index adjustment value can adjust the first respiratory index.

[0075] In this case, the second respiratory index may be multiplied by the weight corresponding to the second respiratory index, and the third respiratory index may be multiplied by the weight corresponding to the third respiratory index, and then the sum is calculated to determine the respiratory index adjustment value. The weight corresponding to the second respiratory index is less than the weight corresponding to the third respiratory index, and both weights are less than 1, and the sum of the weights may be 1 or less than 1.

[0076] It can be understood that the weights corresponding to the second respiratory index and the third respiratory index can be set to different values ​​in combination with different application scenarios, and the values ​​are not specifically limited here.

[0077] Then, the first respiratory index is subtracted from the respiratory index adjustment value, and the value obtained is the target respiratory index. It can be understood that, generally speaking, the ratio of carbon dioxide concentration to oxygen concentration is about 1, and by multiplying by the weight, it can be made less than 1; and the ratio of blood pressure to pulse rate is also between 1 and 2, and by multiplying by the weight, it can be made less than 1. Then, the respiratory index adjustment value finally obtained can play a role in fine-tuning the first respiratory index.

[0078] As a second optional implementation, a target breathing index is determined according to a first breathing index, a second breathing index and a third breathing index, including: obtaining the first breathing index corresponding to multiple historical time points respectively; determining the first breathing index change rate according to the first breathing index corresponding to multiple historical time points and the first breathing index respectively; if the first breathing index change rate is greater than or equal to the preset breathing index change rate, determining the first breathing index as the target breathing index; if the first breathing index change rate is less than the preset breathing index change rate, determining the breathing index adjustment value according to the second breathing index, the weight corresponding to the second breathing index, the third breathing index and the weight corresponding to the third breathing index, wherein the weight corresponding to the second breathing index is less than the weight corresponding to the third breathing index; determining the target breathing index according to the first breathing index and the breathing index adjustment value.

[0079] In this implementation, the first respiratory indexes corresponding to the multiple historical time points can be recorded in the local storage of the ventilator and can be obtained at any time.

[0080] The first respiratory index corresponding to multiple historical time points and the current first respiratory index can be analyzed to determine the change rate of the first respiratory index. For example, the first respiratory index corresponding to multiple historical time points and the current first respiratory index are plotted as a change curve of the respiratory index and time, and then the change rate of the first respiratory index is determined by determining the slope of the change curve.

[0081] Furthermore, the preset breathing index change rate may be 1. Therefore, if the first breathing index change rate is greater than or equal to the preset breathing index change rate, it means that the first breathing index can already reflect the breathing condition well, and the first breathing index can be directly determined as the target breathing index.

[0082] If the first respiratory index change rate is less than the preset respiratory index change rate, it means that the first respiratory index may not reflect the respiratory condition well. Therefore, the respiratory index adjustment value can be determined based on the second respiratory index and the third respiratory index to adjust the first respiratory index.

[0083] Then, the second respiratory index is multiplied by the weight corresponding to the second respiratory index, and the third respiratory index is multiplied by the weight corresponding to the third respiratory index, and then the products obtained are summed to obtain the respiratory index adjustment value. Finally, the respiratory index adjustment value is subtracted from the first respiratory index to obtain the target respiratory index.

[0084] In step 303, a target respiratory symptom type is determined according to the diagnostic data, and the target respiratory symptom type is used to characterize the respiratory symptoms of the ventilator user.

[0085] As an optional implementation, step 303 includes: extracting key diagnostic information corresponding to multiple dimensions from the diagnostic data, the multiple dimensions including: doctor's opinion dimension, patient description information dimension and patient measured data dimension; inputting the key diagnostic information corresponding to the multiple dimensions into the pre-trained prediction model to obtain the prediction information output by the pre-trained prediction model, the prediction information including: spontaneous breathing level and assisted breathing level, different spontaneous breathing levels correspond to different spontaneous breathing capabilities, and different assisted breathing levels correspond to different assisted breathing intensities; determining the target respiratory symptom type according to the spontaneous breathing level and the assisted breathing level.

[0086] Among them, the diagnostic information in the doctor's opinion dimension may be the diagnostic opinion given by the doctor; the diagnostic information in the patient description information dimension may be the disease information described by the patient; and the diagnostic information in the patient's measured data dimension may be the diagnostic result obtained through instrument detection.

[0087] In some embodiments, key information extraction rules may be preconfigured, and then corresponding text processing techniques may be used to extract key information from diagnostic data, wherein the text processing techniques may refer to mature techniques in the art, and the diagnostic data may be in the form of electronic medical records.

[0088] Then, the key diagnostic information corresponding to the multiple dimensions is input into the pre-trained prediction model to obtain the prediction information output by the pre-trained prediction model, which includes: spontaneous breathing level and assisted breathing level. The higher the spontaneous breathing level, the stronger the spontaneous breathing ability. The higher the assisted breathing level, the greater the assisted breathing intensity.

[0089] In the embodiment of the present application, the prediction model may be a large language model.

[0090] As an optional implementation, the training of the prediction model includes: obtaining a training data set, the training data set includes multiple training samples, each training sample includes key diagnostic information, spontaneous breathing level labels and assisted breathing level labels corresponding to multiple dimensions; using the training data set to train the prediction model to obtain a pre-trained prediction model.

[0091] Among them, the spontaneous breathing level labels and assisted breathing level labels in the training samples can be manually marked labels or labels determined according to actual measurement results.

[0092] Furthermore, determining the target respiratory symptom type according to the spontaneous breathing level and the assisted breathing level may include: obtaining a preset respiratory symptom type table, the preset respiratory symptom type table including a plurality of respiratory symptom types and the spontaneous breathing levels and assisted breathing levels corresponding to the plurality of respiratory symptom types, respectively; searching in the preset respiratory symptom type table according to the spontaneous breathing level and the assisted breathing level to determine the target respiratory symptom type.

[0093] For example, it is assumed that the spontaneous breathing level is divided into 3 levels, level 1 represents no spontaneous breathing ability, level 2 represents weak spontaneous breathing ability, and level 3 represents strong spontaneous breathing ability. The assisted breathing level is divided into 2 levels, level 1 represents weakened breathing intensity, and level 2 represents enhanced breathing intensity. Respiratory symptom types include: enhanced spontaneous breathing type, weakened spontaneous breathing type, and enhanced no spontaneous breathing type.

[0094] Then, when the spontaneous breathing level is level 3 and the assisted breathing level is level 1, the respiratory symptom type is the weakened spontaneous breathing type. When the spontaneous breathing level is level 2 and the assisted breathing level is level 1, the respiratory symptom type is the enhanced spontaneous breathing type. When the spontaneous breathing level is level 1 and the assisted breathing level is level 1, the respiratory symptom type is the enhanced non-spontaneous breathing type.

[0095] In step 304, a target oxygen parameter is determined according to the target respiratory index, the target respiratory symptom type and the preset parameter library.

[0096] Among them, by analyzing a large amount of existing ventilator user usage data, the corresponding relationship between the preset respiratory symptom type, the preset respiratory index and the preset oxygen parameter is obtained, and a preset parameter library is generated.

[0097] For example, for a type of respiratory symptom, the ventilator usage data of the ventilator users corresponding to the type of respiratory symptom is obtained, the optimal oxygen parameters under different respiratory conditions are analyzed, and then the respiratory condition is converted into a respiratory index to obtain the corresponding relationship between the respiratory index and the oxygen parameters.

[0098] In some embodiments, when analyzing the optimal oxygen parameters under different breathing conditions, some abnormal data detection algorithms can be used to detect abnormal oxygen parameters, remove these abnormal oxygen parameters, and then determine the optimal oxygen parameters based on the remaining oxygen parameters.

[0099] It is understandable that in addition to the above-mentioned data analysis algorithms, other data analysis algorithms may also be used, which are not limited here.

[0100] Furthermore, the target oxygen parameter can be determined by searching in a preset parameter library according to the target respiratory index and the target respiratory symptom type.

[0101] In step 305, the ventilator is controlled according to the target oxygen parameter.

[0102] In some embodiments, the target oxygen parameter includes multiple oxygen parameters and values ​​corresponding to the multiple oxygen parameters.

[0103] As an optional implementation, step 305 includes: obtaining the current oxygen parameter of the ventilator, determining the oxygen parameter to be adjusted and the parameter adjustment value corresponding to the oxygen parameter to be adjusted according to the current oxygen parameter and the target oxygen parameter; and adjusting the oxygen parameter to be adjusted according to the parameter adjustment value corresponding to the oxygen parameter to be adjusted.

[0104] It can be understood that the oxygen parameter is a plurality of oxygen parameters, some of which may be relatively reasonable and do not need to be adjusted. Whether they are reasonable can refer to the target oxygen parameter. Therefore, the unreasonable oxygen parameter is determined by using the target oxygen parameter, which is the oxygen parameter to be adjusted.

[0105] For example, assuming that there are three parameters, namely oxygen flow rate, oxygen delivery speed and oxygen temperature, the current oxygen flow rate is compared with the target oxygen flow rate. If there is a large difference, the current oxygen flow rate is determined as the oxygen parameter to be adjusted, and the difference between the target oxygen flow rate and the current oxygen flow rate is determined as the parameter adjustment value corresponding to the oxygen parameter to be adjusted. The other two parameters are similar and will not be introduced in detail here.

[0106] As an optional implementation, the control of the ventilator can also be implemented in combination with the instructions of medical staff. Therefore, the respiratory monitoring method also includes: in response to detecting a query request from a medical staff, determining a parameter adjustment item from a preset parameter adjustment library according to the query request, wherein the query request includes monitoring data recorded by the medical staff for the ventilator user, and the preset parameter adjustment library includes: a correspondence between preset monitoring data and preset parameter adjustment items; and feedback parameter adjustment items.

[0107] In this embodiment, a preset parameter adjustment library is also configured, which is obtained by analyzing big data, and includes the correspondence between preset monitoring data and preset parameter adjustment items. For example, every time a patient, a patient's accompanying person or a ward doctor has a ventilator adjustment requirement (including parameter items that need to be adjusted), the ventilator adjustment requirement and the current patient's test data are recorded, so that the data recorded multiple times are integrated to obtain the preset parameter adjustment library. When new data is generated, the preset parameter adjustment library can also be updated.

[0108] Among them, the monitoring data are the monitoring data recorded by medical staff for ventilator users, such as mental state and comfort level.

[0109] Then, the preset parameter adjustment library is searched according to the monitoring data, the parameter adjustment item is determined, and the parameter adjustment item is fed back, for example, by displaying the parameter adjustment item through a display device.

[0110] Thus, step 305 may include: obtaining a parameter adjustment instruction input by the medical staff based on the parameter adjustment item; obtaining the current oxygen parameter of the ventilator; determining the oxygen parameter to be adjusted and the parameter adjustment value corresponding to the oxygen parameter to be adjusted according to the current oxygen parameter, the target oxygen parameter and the parameter adjustment instruction; and controlling the ventilator according to the oxygen parameter to be adjusted and the parameter adjustment value corresponding to the oxygen parameter to be adjusted.

[0111] In some embodiments, the parameter adjustment instruction may include a parameter adjustment item and a corresponding parameter adjustment value.

[0112] Furthermore, first, according to the aforementioned implementation method of determining the oxygen parameter to be adjusted and the parameter adjustment value corresponding to the oxygen parameter to be adjusted based on the current oxygen parameter and the target oxygen parameter, the initial oxygen parameter to be adjusted and the parameter adjustment value corresponding to the oxygen parameter to be adjusted are determined. Then, it is determined whether the oxygen parameter to be adjusted includes the parameter adjustment item in the parameter adjustment instruction. If it does, the corresponding parameter adjustment values ​​are compared to see if they are consistent. If they are inconsistent, the two are averaged to determine the final parameter adjustment value. If not, the corresponding oxygen parameter to be adjusted and the parameter adjustment value are added.

[0113] In the embodiment of the present application, in addition to implementing ventilator control in combination with the instructions of medical staff, ventilator control can also be implemented in combination with other data.

[0114] Therefore, as an optional implementation, the method also includes: obtaining oxygen source monitoring data, the oxygen source monitoring data including oxygen source masses corresponding to multiple monitoring time points; determining oxygen source quality monitoring results based on the oxygen source masses corresponding to the multiple monitoring time points, the oxygen source quality monitoring results being used to characterize whether the oxygen source quality is abnormal.

[0115] Wherein, determining the oxygen source quality monitoring result according to the oxygen source qualities corresponding to the multiple monitoring time points may include: if the oxygen source qualities corresponding to the multiple monitoring time points gradually decrease in chronological order, then determining that the oxygen source quality is abnormal; if the oxygen source qualities corresponding to the multiple monitoring time points remain substantially unchanged in chronological order, then determining that the oxygen source quality is normal.

[0116] Furthermore, step 305 may include: if the oxygen source quality monitoring result indicates that the oxygen source quality is abnormal, feedback prompt information is provided, and the prompt information is used to indicate the optimization of the oxygen source quality; in response to receiving external input information indicating that the oxygen source quality optimization is completed, the ventilator is controlled according to the target oxygen parameter.

[0117] In this embodiment, if the quality of the oxygen source is abnormal, a reminder to optimize the quality of the oxygen source is first given, and after the optimization is completed, the ventilator is controlled according to the target oxygen parameters.

[0118] It can be understood that this embodiment can be used in combination with the aforementioned embodiment, that is, the ventilator can be controlled according to the target oxygen parameters, and can also be combined with the instructions of medical staff.

[0119] As another optional implementation, step 305 includes: obtaining the current oxygen parameter of the ventilator; determining the oxygen parameter to be adjusted and the parameter adjustment value corresponding to the oxygen parameter to be adjusted according to the current oxygen parameter and the target oxygen parameter; if the number of oxygen parameters to be adjusted is less than the preset number, and / or the parameter adjustment value corresponding to the oxygen parameter to be adjusted is less than the preset parameter adjustment value, obtaining noise monitoring data, the noise monitoring data including noise monitoring values ​​corresponding to multiple monitoring time points; determining a denoising strategy according to the noise monitoring data, the denoising strategy being associated with the oxygen parameter adjustment method and / or the heating method of the oxygen heating pipeline of the ventilator; controlling the ventilator according to the oxygen parameter to be adjusted, the parameter adjustment value corresponding to the oxygen parameter to be adjusted and the denoising strategy.

[0120] In this embodiment, the preset number may be half of the total number of oxygen parameters; the preset parameter adjustment value may be an adjustment value indicating that the adjustment will not bring about a significant impact, for example, for oxygen temperature, an adjustment range of 1 to 1.5 degrees will not bring about a significant impact. Specifically, it can be configured according to different application scenarios, for example, in combination with the specific performance of the ventilator, and the value is not specifically limited here.

[0121] Furthermore, if the noise monitoring values ​​corresponding to the multiple monitoring time points gradually increase in chronological order, the denoising strategy may include: the oxygen parameter adjustment method is slow adjustment, and the heating method of the oxygen heating pipeline of the ventilator is slow heating. That is, it is necessary to adopt an oxygen parameter adjustment method and / or an oxygen heating pipeline heating method with less noise.

[0122] If the noise monitoring values ​​corresponding to the respective monitoring time points remain basically unchanged in chronological order, the denoising strategy may include: the oxygen parameter adjustment method is normal adjustment, and the heating method of the oxygen heating pipeline of the ventilator is normal heating. That is, the normal oxygen parameter adjustment method and / or oxygen heating pipeline heating method are adopted.

[0123] Furthermore, combined with the denoising strategy, the oxygen parameter to be adjusted is adjusted according to the parameter adjustment value corresponding to the oxygen parameter to be adjusted, so that the control of the ventilator can be achieved.

[0124] It is understandable that when controlling the ventilator, different control methods can be used for different oxygen parameters. For example, for oxygen flow, if the oxygen flow changes greatly, it may be necessary to remind the user to switch the delivery pipeline. For oxygen delivery speed, the electric valve can be adjusted directly. For oxygen temperature, the heating intensity of the heating pipeline can be adjusted, etc.

[0125] Please refer to Figure 4 , an embodiment of the present application also provides a control device, which can be used as the execution body of the aforementioned respiratory monitoring method.

[0126] The control device includes a processor 401 and a memory 402, and the processor 401 and the memory 402 are communicatively connected.

[0127] The processor 401 and the memory 402 are directly or indirectly electrically connected to each other to realize data transmission or interaction. For example, these elements can be electrically connected through one or more communication buses or signal buses. The method steps executed by the aforementioned modules or interactive terminals respectively include at least one software function module that can be stored in the memory 402 in the form of software or firmware.

[0128] Processor 401 may be an integrated circuit chip with signal processing capability. Processor 401 may be a general-purpose processor, including a CPU (Central Processing Unit), NP (Network Processor), etc.; it may also be a digital signal processor, a dedicated integrated circuit, a readily available programmable gate array or other programmable logic device, a discrete gate or transistor logic device, or a discrete hardware component. It may implement or execute the disclosed methods, steps, and logic block diagrams in the embodiments of the present invention. A general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc.

[0129] The memory 402 can store various software programs and modules. The processor 401 executes various functional applications and data processing by running the software programs and modules stored in the memory 402, that is, implements various steps in the embodiments of the present application.

[0130] The memory 402 may include, but is not limited to, RAM (Random Access Memory), ROM (Read Only Memory), PROM (Programmable Read-Only Memory), EPROM (Erasable Programmable Read-Only Memory), EEPROM (Electric Erasable Programmable Read-Only Memory), etc.

[0131] Understandably, Figure 4 The structure shown is for illustration only. The control device may also include Figure 4 More or fewer components as shown, or with Figure 4 Different configurations are shown.

[0132] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present application may adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program codes.

[0133] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0134] These computer program instructions may also be stored in a computer readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture including an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0135] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0136] The foregoing description of the specific exemplary embodiments of the present application is for the purpose of illustration and illustration. These descriptions are not intended to limit the present application to the precise form disclosed, and it is clear that many changes and variations can be made based on the above teachings. The purpose of selecting and describing the exemplary embodiments is to explain the specific principles of the present application and its practical application, so that those skilled in the art can realize and utilize the various exemplary embodiments of the present application and various selections and changes. The scope of the present application is intended to be limited by the claims and their equivalents.

Claims

1. A ventilator, characterized in that: include: A physiological parameter monitoring device for monitoring the physiological parameters of a ventilator user; An oxygen source monitoring device, used to monitor the quality of the oxygen source; Noise monitoring device, used to monitor noise; Display device; A control device, connected to the physiological parameter monitoring device, the oxygen source monitoring device, the noise monitoring device and the display device respectively; The control device is configured to: obtain physiological parameter monitoring data and diagnostic data of a ventilator user; Determine a target breathing index according to the physiological parameter monitoring data, wherein the target breathing index is used to characterize the breathing stability of the ventilator user; determining a target respiratory symptom type according to the diagnostic data, wherein the target respiratory symptom type is used to characterize the respiratory symptom of the ventilator user; Determining a target oxygen parameter according to the target respiratory index, the target respiratory symptom type and a preset parameter library, wherein the preset parameter library includes: a correspondence between preset respiratory symptom types, preset respiratory indexes and preset oxygen parameters; controlling the ventilator according to the target oxygen parameter; The physiological parameter monitoring data includes: blood oxygen data, pulse rate data, blood pressure data, carbon dioxide data, oxygen concentration data and respiratory rate data. The target respiratory index is determined according to the physiological parameter monitoring data, including: Determine a first respiratory index according to the blood oxygen data, the pulse rate data, the oxygen concentration data and the respiratory frequency data; Determining a second respiratory index according to the carbon dioxide data and the oxygen concentration data; determining a third respiratory index according to the blood pressure data and the pulse rate data; determining a target breathing index according to the first breathing index, the second breathing index, and the third breathing index; Determining a target breathing index according to the first breathing index, the second breathing index, and the third breathing index includes: Obtain first respiratory indexes corresponding to multiple historical time points respectively; Determine a first respiratory index change rate according to the first respiratory indexes respectively corresponding to the multiple historical time points and the first respiratory index; If the first respiratory index change rate is greater than or equal to a preset respiratory index change rate, determining the first respiratory index as a target respiratory index; If the change rate of the first breathing index is less than the preset breathing index change rate, determine the breathing index adjustment value according to the second breathing index, the weight corresponding to the second breathing index, the third breathing index and the weight corresponding to the third breathing index, wherein the weight corresponding to the second breathing index is less than the weight corresponding to the third breathing index; determine the target breathing index according to the first breathing index and the breathing index adjustment value.

2. The ventilator according to claim 1, characterized in that: The oxygen parameter includes oxygen flow rate, and the control device is further configured to: Acquire operation information of the ventilator, the operation information including a current operation mode and an operation duration of the current operation mode, different operation modes correspond to different oxygen flow thresholds; Correspondingly, the step of obtaining the physiological parameter monitoring data and diagnostic data of the ventilator user includes: If the running time of the current running mode is greater than the preset running time, or the running time of the current running mode is less than or equal to the preset running time, and the difference between the oxygen flow threshold value corresponding to the current running mode and the oxygen flow threshold value corresponding to the previous running mode is greater than the preset difference, the physiological parameter monitoring data and diagnostic data of the ventilator user are obtained.

3. The ventilator according to claim 1, characterized in that: The control device is also configured to: Comparing the first respiratory index with a preset respiratory index range to obtain a comparison result; If the first breathing index is within the preset breathing index range, determining a breathing index adjustment value according to the second breathing index, a weight corresponding to the second breathing index, and the third breathing index; If the first respiratory index is not within the preset respiratory index range, determining a respiratory index adjustment value according to the second respiratory index, the weight corresponding to the second respiratory index, the third respiratory index, and the weight corresponding to the third respiratory index, wherein the weight corresponding to the second respiratory index is less than the weight corresponding to the third respiratory index; The target breathing index is determined according to the first breathing index and the breathing index adjustment value.

4. The ventilator according to claim 1, characterized in that: The control device is also configured to: Extracting key diagnostic information corresponding to multiple dimensions from the diagnostic data, wherein the multiple dimensions include: a doctor's opinion dimension, a patient description information dimension, and a patient's measured data dimension; Inputting the key diagnostic information corresponding to the multiple dimensions into a pre-trained prediction model to obtain prediction information output by the pre-trained prediction model, wherein the prediction information includes: a spontaneous breathing level and an assisted breathing level, wherein different spontaneous breathing levels correspond to different spontaneous breathing capabilities, and different assisted breathing levels correspond to different assisted breathing intensities; The target respiratory symptom type is determined according to the spontaneous breathing level and the assisted breathing level.

5. The ventilator according to claim 1, characterized in that: The control device is also configured to: In response to detecting a query request from a medical staff, determining a parameter adjustment item from a preset parameter adjustment library according to the query request, wherein the query request includes monitoring data recorded by the medical staff for a ventilator user, and the preset parameter adjustment library includes: a correspondence between preset monitoring data and preset parameter adjustment items; Feedback of the parameter adjustment item; Correspondingly, controlling the ventilator according to the target oxygen parameter includes: Acquiring a parameter adjustment instruction input by the medical staff based on the parameter adjustment item; Obtaining current oxygen parameters of the ventilator; Determining, according to the current oxygen parameter, the target oxygen parameter and the parameter adjustment instruction, the oxygen parameter to be adjusted and the parameter adjustment value corresponding to the oxygen parameter to be adjusted; The ventilator is controlled according to the oxygen parameter to be adjusted and the parameter adjustment value corresponding to the oxygen parameter to be adjusted.

6. The ventilator according to claim 1, characterized in that: The control device is also configured to: Acquiring oxygen source monitoring data, wherein the oxygen source monitoring data includes oxygen source masses corresponding to a plurality of monitoring time points respectively; Determining an oxygen source quality monitoring result according to the oxygen source qualities corresponding to the plurality of monitoring time points, wherein the oxygen source quality monitoring result is used to indicate whether the oxygen source quality is abnormal; Correspondingly, controlling the ventilator according to the target oxygen parameter includes: If the oxygen source quality monitoring result indicates that the oxygen source quality is abnormal, feedback prompt information is provided, and the prompt information is used to indicate the optimization of the oxygen source quality; In response to receiving external input information indicating that the oxygen source quality optimization is completed, the ventilator is controlled according to the target oxygen parameter.

7. The ventilator according to claim 1, characterized in that: The control device is also configured to: Obtaining current oxygen parameters of the ventilator; Determining, according to the current oxygen parameter and the target oxygen parameter, an oxygen parameter to be adjusted and a parameter adjustment value corresponding to the oxygen parameter to be adjusted; If the number of the oxygen parameters to be adjusted is less than the preset number, and / or the parameter adjustment value corresponding to the oxygen parameter to be adjusted is less than the preset parameter adjustment value, obtaining noise monitoring data, wherein the noise monitoring data includes noise monitoring values ​​corresponding to a plurality of monitoring time points respectively; Determining a denoising strategy according to the noise monitoring data, wherein the denoising strategy is associated with an oxygen parameter adjustment method and / or a heating method of an oxygen heating pipeline of the ventilator; The ventilator is controlled according to the oxygen parameter to be adjusted, the parameter adjustment value corresponding to the oxygen parameter to be adjusted, and the denoising strategy.

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