A respiratory recognition method and device, a ventilation device, and a storage medium

Abstract

The embodiment of the application discloses a respiration recognition method, which is applied to a ventilation device. The method comprises the following steps: acquiring airway pressure and gas flow rate in the process of mechanical ventilation; determining cross-correlation data corresponding to the airway pressure and the gas flow rate according to the airway pressure and the gas flow rate; and recognizing the respiration state of a patient according to the change of the cross-correlation data.

Description

[0001] Case Analysis

[0002] This application is a divisional application of Chinese patent application No. 201880098692.4, which entered the Chinese national phase of PCT international patent application PCT / CN2018 / 114635, filed on November 8, 2018, and entitled "A Breathing Recognition Method and Device, Ventilation Equipment, and Storage Medium". Technical Field

[0003] The embodiments of the present invention relate to the field of medical device technology, and in particular to a breathing recognition method and device, ventilation equipment, and storage medium. Background Technology

[0004] During the mechanical ventilation of patients, ventilation equipment such as ventilators and anesthesia machines need to perform real-time respiratory recognition to determine whether the patient is experiencing suffocation or to trigger the corresponding ventilation mode to achieve human-machine synchronization.

[0005] Currently, there are several methods for respiratory recognition: one is based on diaphragmatic electrical activity, which measures the electrical activity of the diaphragm to determine the patient's breathing; the other is based on abdominal sensors, which monitors the patient's abdominal movements to identify whether the patient is breathing spontaneously.

[0006] However, the above-mentioned breathing recognition methods may be affected by external factors, the ventilation equipment itself, or the difficulty of testing, which may lead to inaccurate breathing recognition or even misrecognition. Summary of the Invention

[0007] To address the aforementioned technical problems, embodiments of the present invention aim to provide a respiratory recognition method and device, ventilation equipment, and storage medium that can identify a patient's respiratory status based on changes in the cross-correlation data of airway pressure and gas flow rate during mechanical ventilation, thereby effectively reducing the impact of interference signals on respiratory recognition and improving the accuracy of respiratory recognition.

[0008] The technical solution of this invention can be implemented as follows:

[0009] This invention provides a breathing recognition method applied to ventilation equipment, the method comprising:

[0010] During mechanical ventilation, airway pressure and gas flow rate are measured.

[0011] Based on the airway pressure and the gas flow rate, determine the cross-correlation data corresponding to the airway pressure and the gas flow rate;

[0012] The patient's respiratory status is identified based on changes in the cross-correlation data.

[0013] In the above scheme, determining the cross-correlation data corresponding to the airway pressure and the gas flow rate based on the airway pressure and the gas flow rate includes:

[0014] According to the preset signal sampling rate and preset sampling time, the cross-correlation calculation is performed on the airway pressure and the gas flow rate to obtain the cross-correlation data.

[0015] In the above scheme, the step of performing cross-correlation calculations on the airway pressure and the gas flow rate according to a preset signal sampling rate and a preset sampling time to obtain the cross-correlation data includes:

[0016] Based on the preset signal sampling rate, the first sampling value corresponding to the airway pressure and the second sampling value corresponding to the gas flow rate are obtained within the preset sampling time.

[0017] The cross-correlation data is obtained by performing cross-correlation calculations on the first sampled value and the second sampled value.

[0018] In the above scheme, the patient's respiratory status includes spontaneous inhalation and / or spontaneous exhalation. After identifying the patient's respiratory status based on changes in the cross-correlation data, the method further includes:

[0019] The ventilation device is controlled to switch ventilation modes based on the identified patient's respiratory status.

[0020] In the above scheme, the step of controlling the ventilation device to switch ventilation modes based on the identified patient's respiratory status includes:

[0021] If the patient's breathing state changes from spontaneous exhalation to spontaneous inhalation, the ventilation device is triggered to enter the inspiratory ventilation mode;

[0022] If the patient's breathing state changes from spontaneous inhalation to spontaneous exhalation, the ventilation device is triggered to enter the expiratory ventilation mode.

[0023] In the above scheme, the gas flow rate is the respiratory flow rate, and the step of identifying the patient's respiratory status based on the changes in the cross-correlation data includes:

[0024] If the cross-correlation data is greater than the first preset threshold, the patient's breathing state is determined to be spontaneous inhalation;

[0025] If the cross-correlation data is less than the second preset threshold, the patient's breathing state is determined to be spontaneous exhalation.

[0026] In the above scheme, the gas flow rate is the delivery gas flow rate, and the step of identifying the patient's respiratory status based on the changes in the cross-correlation data includes:

[0027] Determine the parameter baseline corresponding to the cross-correlation data;

[0028] If the cross-correlation data is greater than the parameter baseline, and the difference between the cross-correlation data and the parameter baseline is greater than a third preset threshold, then the patient's breathing state is determined to be spontaneous exhalation.

[0029] If the cross-correlation data is less than the parameter baseline, and the difference between the cross-correlation data and the parameter baseline is greater than a fourth preset threshold, then the patient's breathing state is determined to be spontaneous inhalation.

[0030] In the above scheme, the step of determining the parameter baseline corresponding to the cross-correlation data includes:

[0031] Calculate the cross-correlation data within the first time period;

[0032] The cross-correlation data within the first time period is low-pass filtered to obtain the parameter baseline.

[0033] In the above scheme, the patient's respiratory state includes asphyxia, and the step of identifying the patient's respiratory state based on changes in the cross-correlation data includes:

[0034] If the fluctuation range of the cross-correlation data is less than a preset fluctuation range threshold, the patient's respiratory state is determined to be asphyxiation.

[0035] In the above protocol, the patient's respiratory status includes assisted inhalation and / or assisted exhalation.

[0036] In the above scheme, after identifying the patient's respiratory status based on the changes in the cross-correlation data, the method further includes:

[0037] The system compares whether the identified patient's respiratory status matches the current ventilation mode of the ventilation device and outputs the comparison result.

[0038] In the above scheme, the gas flow rate is the respiratory flow rate, and the step of identifying the patient's respiratory status based on the changes in the cross-correlation data includes:

[0039] If the cross-correlation data is greater than zero, the patient's respiratory state is determined to be assisted inspiration;

[0040] If the cross-correlation data is less than zero, the patient's respiratory state is determined to be assisted exhalation.

[0041] In the above scheme, the gas flow rate is the delivery gas flow rate, and the step of identifying the patient's respiratory status based on the changes in the cross-correlation data includes:

[0042] If the cross-correlation data increases, the patient's respiratory status is determined to be assisted inspiration;

[0043] If the cross-correlation data decreases, the patient's respiratory status is determined to be assisted exhalation.

[0044] This invention provides a breathing recognition device, the device comprising:

[0045] The acquisition module acquires airway pressure and gas flow rate during mechanical ventilation; the gas flow rate is the respiratory flow rate or the delivery flow rate.

[0046] The processing module determines the cross-correlation data corresponding to the airway pressure and the gas flow rate based on the airway pressure and the gas flow rate; and identifies whether spontaneous breathing occurs based on the changes in the cross-correlation data.

[0047] In the above-mentioned device, the processing module performs cross-correlation calculations on the airway pressure and the gas flow rate according to a preset signal sampling rate and a preset sampling time to obtain the cross-correlation data.

[0048] In the above device, the processing module acquires a first sampled value corresponding to the airway pressure and a second sampled value corresponding to the gas flow rate within the preset sampling time, according to the preset signal sampling rate; and performs cross-correlation calculation on the first sampled value and the second sampled value to obtain the cross-correlation data.

[0049] In the aforementioned device, the patient's respiratory state includes spontaneous inhalation and / or spontaneous exhalation.

[0050] After identifying the patient's respiratory status based on the changes in the cross-correlation data, the processing module controls the ventilation device to switch ventilation modes according to the identified patient's respiratory status.

[0051] In the above-described device, the step of the processing module controlling the ventilation device to switch ventilation modes based on the identified patient's respiratory status includes:

[0052] If the patient's breathing state changes from spontaneous exhalation to spontaneous inhalation, the ventilation device is triggered to enter the inspiratory ventilation mode;

[0053] If the patient's breathing state changes from spontaneous inhalation to spontaneous exhalation, the ventilation device is triggered to enter the expiratory ventilation mode.

[0054] In the above device, the gas flow rate is the respiratory flow rate, and the step of the processing module identifying the patient's respiratory status based on the changes in the cross-correlation data includes:

[0055] If the cross-correlation data is greater than the first preset threshold, the patient's breathing state is determined to be spontaneous inhalation;

[0056] If the cross-correlation data is less than the second preset threshold, the patient's breathing state is determined to be spontaneous exhalation.

[0057] In the above device, the gas flow rate is the delivery gas flow rate, and the step of the processing module identifying the patient's respiratory status based on the changes in the cross-correlation data includes:

[0058] Determine the parameter baseline corresponding to the cross-correlation data;

[0059] If the cross-correlation data is greater than the parameter baseline, and the difference between the cross-correlation data and the parameter baseline is greater than a third preset threshold, then the patient's breathing state is determined to be spontaneous exhalation.

[0060] If the cross-correlation data is less than the parameter baseline, and the difference between the cross-correlation data and the parameter baseline is greater than a fourth preset threshold, then the patient's breathing state is determined to be spontaneous inhalation.

[0061] In the above apparatus, the step of the processing module determining the parameter baseline corresponding to the cross-correlation data includes:

[0062] Calculate the cross-correlation data within the first time period;

[0063] The cross-correlation data within the first time period is low-pass filtered to obtain the parameter baseline.

[0064] In the above-described device, the patient's respiratory state includes asphyxiation, and the step of the processing module identifying the patient's respiratory state based on changes in the cross-correlation data includes:

[0065] If the fluctuation range of the cross-correlation data is less than a preset fluctuation range threshold, the patient's respiratory state is determined to be asphyxiation.

[0066] In the above-described device, the patient's respiratory state includes assisted inhalation and / or assisted exhalation.

[0067] In the above device, after the processing module identifies the patient's respiratory status based on the changes in the cross-correlation data, it compares whether the identified patient's respiratory status matches the current ventilation mode of the ventilation device and outputs the comparison result.

[0068] In the above device, the gas flow rate is the respiratory flow rate, and the step of the processing module identifying the patient's respiratory status based on the changes in the cross-correlation data includes:

[0069] If the cross-correlation data is greater than zero, the patient's respiratory state is determined to be assisted inspiration;

[0070] If the cross-correlation data is less than zero, the patient's respiratory state is determined to be assisted exhalation.

[0071] In the above device, the gas flow rate is the delivery gas flow rate, and the step of the processing module identifying the patient's respiratory status based on the changes in the cross-correlation data includes:

[0072] If the cross-correlation data increases, the patient's respiratory status is determined to be assisted inspiration;

[0073] If the cross-correlation data decreases, the patient's respiratory status is determined to be assisted exhalation.

[0074] This invention provides a ventilation device including the above-described respiratory recognition device, comprising an air source, a breathing tubing, a display, and a controller;

[0075] The gas source provides gas during mechanical ventilation;

[0076] The breathing tubing is connected to the air source and provides inhalation and exhalation pathways during the mechanical ventilation process;

[0077] The breathing recognition device is connected to the breathing tubing and the controller;

[0078] The respiratory recognition device identifies the patient's respiratory status during the mechanical ventilation process;

[0079] The controller is also connected to the air source to control the mechanical ventilation process;

[0080] The display is connected to the controller and displays the respiratory waveform during mechanical ventilation.

[0081] This invention provides a computer-readable storage medium storing a breathing recognition program that can be executed by a processor to implement the breathing recognition method described above.

[0082] Therefore, in the technical solution of this invention embodiment, during mechanical ventilation, airway pressure and gas flow rate are acquired; based on the airway pressure and gas flow rate, cross-correlation data corresponding to the airway pressure and gas flow rate are determined; and the patient's respiratory status is identified based on changes in the cross-correlation data. In other words, the technical solution provided by this invention embodiment can identify the patient's respiratory status based on changes in the cross-correlation data of airway pressure and gas flow rate during mechanical ventilation, thereby effectively reducing the impact of interference signals on respiratory recognition and improving the accuracy of respiratory recognition. Attached Figure Description

[0083] Figure 1 This is a schematic flowchart of a breathing recognition method provided in an embodiment of the present invention;

[0084] Figure 2(a) is a schematic diagram of an exemplary respiratory flow rate provided in an embodiment of the present invention;

[0085] Figure 2(b) is a schematic diagram of an exemplary airway pressure waveform provided by an embodiment of the present invention. Figure 1 ;

[0086] Figure 2(c) is a waveform diagram of an exemplary cross-correlation data provided in an embodiment of the present invention. Figure 1 ;

[0087] Figure 3(a) is a waveform diagram of an exemplary airflow velocity provided in an embodiment of the present invention;

[0088] Figure 3(b) is a schematic diagram of an exemplary airway pressure waveform provided in an embodiment of the present invention;

[0089] Figure 3(c) is a schematic diagram of an exemplary cross-correlation data provided in an embodiment of the present invention;

[0090] Figure 4(a) is a waveform diagram of the air supply velocity when water accumulates in a pipeline, as provided in an embodiment of the present invention.

[0091] Figure 4(b) is a schematic diagram of the airway pressure waveform when water accumulates in a pipeline, as provided in an embodiment of the present invention.

[0092] Figure 4(c) is a waveform diagram of cross-correlation data for an exemplary pipeline water accumulation according to an embodiment of the present invention;

[0093] Figure 5 A schematic diagram of an exemplary parameter baseline provided for an embodiment of the present invention;

[0094] Figure 6 This is a schematic diagram of the structure of a breathing recognition device provided in an embodiment of the present invention;

[0095] Figure 7 This is a schematic diagram of a ventilation device provided in an embodiment of the present invention. Detailed Implementation

[0096] To gain a more detailed understanding of the features and technical content of the embodiments of the present invention, the implementation of the embodiments of the present invention will be described in detail below with reference to the accompanying drawings. The accompanying drawings are for reference and illustration only and are not intended to limit the embodiments of the present invention.

[0097] This invention provides a breathing recognition method applied to ventilation equipment. It should be noted that, in this embodiment, the breathing recognition method is executed by a breathing recognition device. Figure 6 This is a schematic diagram of a breathing recognition device provided in an embodiment of the present invention. Figure 6 As shown, the breathing recognition device includes an acquisition module 601 and a processing module 602. The breathing recognition method of the present invention will be described below based on this breathing recognition device.

[0098] Figure 1 This is a schematic flowchart illustrating a breathing recognition method provided in an embodiment of the present invention. Figure 1 As shown, the breathing recognition method mainly includes the following steps:

[0099] S101. During mechanical ventilation, obtain airway pressure and gas flow rate.

[0100] In an embodiment of the present invention, the acquisition module 601 in the breathing recognition device can acquire airway pressure and gas flow rate in real time during mechanical ventilation.

[0101] It should be noted that, in the embodiments of the present invention, the gas flow rate is the delivery flow rate or the breathing flow rate, and the specific gas flow rate is not limited in the embodiments of the present invention.

[0102] It should be noted that, in the embodiments of the present invention, the ventilation device can be a medical device with ventilation function, such as a ventilator or anesthesia machine, including a respiratory recognition device. The specific ventilation device is not limited in the embodiments of the present invention.

[0103] It should be noted that, in the embodiments of the present invention, the acquisition module 601 continuously acquires the airway pressure and gas flow rate. That is, from the beginning to the end of mechanical ventilation, the acquisition module 601 is always acquiring the airway pressure and gas flow rate.

[0104] It is understood that, in the embodiments of the present invention, the breathing circuit of the ventilation device may be provided with an acquisition module 601, and the acquisition module 601 may specifically include different sensors, such as pressure sensors and flow sensors, for real-time acquisition of airway pressure and gas flow rate. The specific method of acquiring airway pressure and gas flow rate is not limited in the embodiments of the present invention.

[0105] S102. Determine the cross-correlation data corresponding to airway pressure and gas flow rate based on airway pressure and gas flow rate.

[0106] In an embodiment of the present invention, after the acquisition module 601 in the breathing recognition device acquires the airway pressure and gas flow rate, the processing module 602 can determine the cross-correlation data corresponding to the airway pressure and gas flow rate based on the airway pressure and gas flow rate.

[0107] In an embodiment of the present invention, the processing module 602 determines the cross-correlation data corresponding to the airway pressure and the gas flow rate based on the airway pressure and the gas flow rate, including: performing cross-correlation calculation on the airway pressure and the gas flow rate according to a preset signal sampling rate and a preset sampling time to obtain the cross-correlation data.

[0108] It should be noted that, in the embodiments of the present invention, medical personnel can determine the signal sampling rate and sampling time according to actual needs, and set the determined signal sampling rate and sampling time in the processing module 602. That is, the processing module 602 can pre-store the preset signal sampling rate and preset sampling time. The specific preset signal sampling rate and preset sampling time are not limited in the embodiments of the present invention.

[0109] Specifically, in an embodiment of the present invention, the processing module 602 performs cross-correlation calculations on airway pressure and gas flow rate according to a preset signal sampling rate and a preset sampling time to obtain cross-correlation data, including: obtaining a first sampling value corresponding to airway pressure and a second sampling value corresponding to gas flow rate within a preset sampling time according to the preset signal sampling rate; and performing cross-correlation calculations on the first sampling value and the second sampling value to obtain cross-correlation data.

[0110] It should be noted that, in the embodiments of the present invention, the preset signal sampling rate can represent the number of airway pressure values ​​and the number of gas flow rate values ​​that can be acquired within 1 second, while the preset sampling time specifically limits the acquisition time. That is, if the preset signal sampling rate is 1kHz and the preset sampling time is 20ms, the preset signal sampling rate of 1kHz means that 1000 sample values ​​corresponding to airway pressure and 1000 sample values ​​corresponding to gas flow rate can be acquired within 1 second. The limitation of the preset sampling time of 20ms means that the processing module 602 actually acquires the data through the acquisition module 6... 01. The airway pressure and gas flow rate are acquired over 20 ms. Therefore, based on the preset signal sampling rate of 1 kHz, the processing module 602 can acquire 20 sampled values ​​corresponding to the airway pressure and 20 sampled values ​​corresponding to the gas flow rate within 20 ms through the acquisition module 601. The 20 sampled values ​​corresponding to the airway pressure are the first sampled values, and the 20 sampled values ​​corresponding to the gas flow rate are the second sampled values. Then, the first sampled values ​​and the second sampled values ​​can be cross-correlated to each other to obtain the cross-correlation data of the airway pressure and gas flow rate at a certain moment.

[0111] It is understood that in the embodiments of the present invention, the number of the first sample value and the second sample value is determined by the preset signal sampling rate and the preset sampling time. There can be multiple values, but the number of the two values ​​is the same and they correspond one-to-one. That is, when a first sample value is acquired at a certain moment of the preset sampling time, a corresponding second sample value will be acquired at the same time.

[0112] For example, in an embodiment of the present invention, the preset signal sampling rate is 1kHz and the preset sampling time is 20ms. The processing module 602 can calculate the cross-correlation data between airway pressure and gas flow rate according to Formula 1:

[0113]

[0114] Where Corr(k) represents the cross-correlation data of airway pressure and gas flow rate at time k, Flow(i) represents the gas flow rate at time i, and Pressure(i) represents the airway pressure at time i.

[0115] It is understood that in the embodiments of the present invention, the preset signal sampling rate is 1kHz and the preset sampling time is 20ms. Therefore, the processing module 602 actually obtains 20 first sampling values ​​corresponding to the airway pressure and 20 first sampling values ​​corresponding to the gas flow rate. Therefore, when calculating the cross-correlation data of airway pressure and gas flow rate at a certain moment, such as moment k, the airway pressure and gas flow rate at moment k, as well as the airway pressure and gas flow rate at the previous 19 moments, can be substituted into Formula 1 to calculate and obtain the cross-correlation data of airway pressure and gas flow rate at moment k.

[0116] Figure 2(a) is a schematic diagram of an exemplary respiratory flow rate provided in an embodiment of the present invention. Figure 2(b) is a schematic diagram of an exemplary airway pressure provided in an embodiment of the present invention. Figure 1 Figure 2(c) is a waveform diagram of exemplary cross-correlation data provided in an embodiment of the present invention. Figure 1 As shown in Figure 2(a), the gas flow rate is the respiratory flow rate. If the preset signal sampling rate is 1kHz and the preset sampling time is 20ms, the processing module 602 performs the above-mentioned cross-correlation calculation between the respiratory flow rate shown in Figure 2(a) and the airway pressure shown in Figure 2(b), and can obtain the cross-correlation data shown in Figure 2(c).

[0117] Figure 3(a) is a waveform diagram of an exemplary gas flow rate provided in an embodiment of the present invention. Figure 3(b) is a waveform diagram of an exemplary airway pressure provided in an embodiment of the present invention. Figure 3(c) is a waveform diagram of an exemplary cross-correlation data provided in an embodiment of the present invention. As shown in Figure 3(a), the gas flow rate is the gas flow rate. If the preset signal sampling rate is 1kHz and the preset sampling time is 20ms, the processing module 602 performs the above-mentioned cross-correlation calculation on the gas flow rate shown in Figure 3(a) and the airway pressure shown in Figure 3(b) to obtain the cross-correlation data shown in Figure 3(c).

[0118] Figure 4(a) is a waveform diagram of the airflow velocity when the pipeline is filled with water, as provided in an embodiment of the present invention. Figure 4(b) is a waveform diagram of the airway pressure when the pipeline is filled with water, as provided in an embodiment of the present invention. Figure 4(c) is a waveform diagram of cross-correlation data when the pipeline is filled with water, as provided in an embodiment of the present invention. When the pipeline of the ventilation device is filled with water, the water in the pipeline flows due to the airflow, which causes frequent fluctuations in the airflow velocity and airway pressure, as shown in Figures 4(a) and 4(b). These fluctuations are superimposed on the waveforms of the airflow velocity and airway pressure, making it difficult to identify the patient's respiratory status. However, if the processing module 602 performs cross-correlation calculation on the airflow velocity shown in Figure 4(a) and the airway pressure shown in Figure 4(b) according to the above cross-correlation formula, the waveform diagram shown in Figure 4(c) can be obtained, which can clearly identify the patient's respiratory status.

[0119] Understandably, in existing technologies, respiratory identification is usually based on only one of airway pressure and gas flow rate. However, changes in airway pressure and gas flow rate are often not significant enough and are easily affected by other factors, making accurate identification difficult. In the embodiments of the present invention, considering that changes in airway pressure and gas flow rate are opposite, cross-correlation data corresponding to airway pressure and gas flow rate are calculated. As can be clearly seen from Figures 2(c), 3(c), and 4(c), the cross-correlation data can clearly characterize the fluctuations in the patient's breathing. In fact, the cross-correlation data can amplify the amplitude of small respiratory fluctuations, thus enabling more accurate identification of the patient's respiratory status.

[0120] S103. Identify the patient's respiratory status based on changes in cross-correlation data.

[0121] In an embodiment of the present invention, after determining the cross-correlation data corresponding to airway pressure and gas flow rate, the processing module 602 in the respiratory recognition device can identify the patient's respiratory status based on the changes in the cross-correlation data.

[0122] It should be noted that, in the embodiments of the present invention, the patient's respiratory state includes: spontaneous inhalation, spontaneous exhalation, asphyxia, assisted inhalation, and assisted exhalation. The processing module 602 can identify the specific patient's respiratory state based on changes in cross-correlation data.

[0123] Specifically, in an embodiment of the present invention, if the gas flow rate is the respiratory flow rate, the step of the processing module 602 identifying the patient's respiratory state based on the change in cross-correlation data includes: if the cross-correlation data is greater than a first preset threshold, then the patient's respiratory state is determined to be spontaneous inhalation; if the cross-correlation data is less than a second preset threshold, then the patient's respiratory state is determined to be spontaneous exhalation.

[0124] It should be noted that, in this embodiment of the invention, the processing module 602 stores a first preset threshold and a second preset threshold, the first preset threshold being greater than the second preset threshold, and the specific first preset threshold and the second preset threshold are not limited in this embodiment of the invention.

[0125] For example, in an embodiment of the present invention, the gas flow rate is the respiratory flow rate, that is, the processing module 602 can determine the cross-correlation data corresponding to the respiratory flow rate and the airway pressure in real time. The first preset threshold is A1 and the second preset threshold is A2. If the cross-correlation data corresponding to the respiratory flow rate and the airway pressure is greater than A1, the patient's breathing state is determined to be spontaneous inhalation. If the cross-correlation data corresponding to the respiratory flow rate and the airway pressure is less than A2, the patient's breathing state is determined to be spontaneous exhalation.

[0126] It is understood that, in the embodiments of the present invention, during mechanical ventilation, if the patient inhales spontaneously, the airway pressure will decrease. At this time, in order to meet the patient's inhalation needs, the delivery flow rate or respiratory flow rate will increase. That is, the gas flow rate and airway pressure are out of phase. Similarly, if the patient exhales spontaneously, the two are also out of phase. Therefore, by using the changes in the cross-correlation data corresponding to gas flow rate and airway pressure, spontaneous inhalation and spontaneous exhalation can be clearly identified.

[0127] It should be noted that, in the embodiments of the present invention, under normal circumstances, the respiratory flow rate is greater than zero during the inhalation phase and less than zero during the exhalation phase, while the airway pressure is greater than zero. Therefore, when the processing module 602 determines spontaneous inhalation and spontaneous exhalation based on the cross-correlation data corresponding to the respiratory flow rate and airway pressure, it can determine spontaneous inhalation when the cross-correlation data is greater than a certain threshold, i.e., the first preset threshold, and determine spontaneous exhalation when the cross-correlation data is less than a certain threshold, i.e., the second preset threshold.

[0128] Specifically, in an embodiment of the present invention, if the gas flow rate is the delivery gas flow rate, the step of the processing module 602 in identifying the patient's respiratory state based on the change in cross-correlation data includes: determining the parameter baseline corresponding to the cross-correlation data; if the cross-correlation data is greater than the parameter baseline, and the difference between the cross-correlation data and the parameter baseline is greater than a third preset threshold, then the patient's respiratory state is determined to be spontaneous exhalation; if the cross-correlation data is less than the parameter baseline, and the difference between the cross-correlation data and the parameter baseline is greater than a fourth preset threshold, then the patient's respiratory state is determined to be spontaneous inhalation.

[0129] It should be noted that, in the embodiments of the present invention, the processing module 602 stores a third preset threshold and a fourth preset threshold, and the specific third preset threshold and the fourth preset threshold are not limited in the embodiments of the present invention.

[0130] It should be noted that, in the embodiments of the present invention, if the gas flow rate is the supply gas flow rate, the processing module 602 needs to first determine the parameter baseline corresponding to the cross-correlation data of the supply gas flow rate and the airway pressure, including: calculating the cross-correlation data within a first time period; performing low-pass filtering on the cross-correlation data within the first time period to obtain the parameter baseline.

[0131] It should be noted that, in the embodiments of the present invention, the first time period can be a relatively long time period preset by medical personnel in the processing module 602. The processing module 602 can calculate the cross-correlation data corresponding to the airway flow rate and airway pressure within the first time period, perform low-pass filtering on the cross-correlation data within this time period, thereby filtering out the fluctuation amplitude and obtaining a reference baseline, which is the parameter baseline. The specific first time period is not limited in the embodiments of the present invention.

[0132] Figure 5 This is a schematic diagram of an exemplary parameter baseline provided for an embodiment of the present invention. For example... Figure 5 As shown, the first time period is 1000ms. The solid line represents the cross-correlation data of the airflow velocity and airway pressure within 1000ms. After low-pass filtering the cross-correlation data, the parameter baseline shown by the dashed line can be obtained.

[0133] It should be noted that, in the embodiments of the present invention, the processing module 602 may further calculate the mean value of the cross-correlation data corresponding to the airflow velocity and airway pressure within the first time period, and determine the mean value as the parameter baseline.

[0134] For example, in an embodiment of the present invention, the gas flow rate is the delivery gas flow rate, and the processing module 602 determines the parameter baseline as... Figure 5 Following the dashed line, the cross-correlation data corresponding to the airway pressure can be determined in real time. The third preset threshold is A3, and the fourth preset threshold is A4. If the cross-correlation data corresponding to the airway pressure is greater than the parameter baseline and the difference between the two is greater than A3, the patient's breathing state is determined to be spontaneous exhalation. If the cross-correlation data corresponding to the airway pressure is less than the parameter baseline and the difference between the two is greater than A4, the patient's breathing state is determined to be spontaneous inhalation.

[0135] It should be noted that, in the embodiments of the present invention, under normal circumstances, the airflow rate is greater than zero, the airway pressure is also greater than zero, and the actual parameter baseline is greater than zero. Based on the relationship between airflow rate and airway pressure, it is known that when the cross-correlation data is less than the parameter baseline, it is the inhalation phase, and when it is greater than the parameter baseline, it is the exhalation phase. Therefore, when the processing module 602 determines spontaneous inhalation and spontaneous exhalation based on the cross-correlation data corresponding to the airflow rate and airway pressure, it can determine spontaneous exhalation when the cross-correlation data is greater than the parameter baseline by a certain threshold, i.e., the third preset threshold, and determine spontaneous inhalation when the cross-correlation data is less than the parameter baseline by a certain threshold, i.e., the fourth preset threshold.

[0136] It should be noted that, in the embodiments of the present invention, after the processing module 602 identifies the patient's breathing state as spontaneous inhalation or spontaneous exhalation, it can also control the ventilation device to switch the ventilation mode according to the identified patient's breathing state.

[0137] Specifically, in an embodiment of the present invention, the step of the processing module 602 controlling the ventilation device to switch ventilation modes according to the identified patient's respiratory state includes: if the patient's respiratory state changes from spontaneous exhalation to spontaneous inhalation, the ventilation device is triggered to enter the inspiratory ventilation mode; if the patient's respiratory state changes from spontaneous inhalation to spontaneous exhalation, the ventilation device is triggered to enter the expiratory ventilation mode.

[0138] It should be noted that, in the embodiments of the present invention, the processing module 602 can trigger the ventilation device to enter the inspiratory ventilation mode or the expiratory ventilation mode by outputting a corresponding control signal to the controller of the ventilation device. The controller can then control the device to enter the inspiratory ventilation mode or the expiratory ventilation mode according to the control signal. The specific triggering method is not limited in the embodiments of the present invention.

[0139] Specifically, in an embodiment of the present invention, the patient's respiratory state includes asphyxiation. The step of the processing module 602 in identifying the patient's respiratory state based on the changes in cross-correlation data includes: if the fluctuation amplitude of the cross-correlation data is less than a preset fluctuation amplitude threshold, then the patient's respiratory state is determined to be asphyxiation.

[0140] It should be noted that, in the embodiments of the present invention, the processing module 602 stores a preset fluctuation range, and medical staff can adjust the preset fluctuation range according to actual needs. The specific preset fluctuation range is not limited in the embodiments of the present invention.

[0141] It is understood that in the embodiments of the present invention, if the patient's breathing state is asphyxiation, that is, unable to breathe normally, the gas flow rate and airway pressure remain basically unchanged, and the cross-correlation data will not fluctuate, thereby identifying that the patient is asphyxiating.

[0142] It should be noted that, in the embodiments of the present invention, the cross-correlation data used by the processing module 602 to identify asphyxiation can be cross-correlation data corresponding to respiratory flow rate and airway pressure, or cross-correlation data corresponding to airway flow rate and airway pressure. As long as the fluctuation amplitude is less than the preset fluctuation amplitude threshold, the patient's respiratory state can be identified as asphyxiation.

[0143] Specifically, in embodiments of the present invention, the patient's respiratory state includes assisted inspiration and / or assisted expiration. If the gas flow rate is the respiratory flow rate, the step of the processing module 602 in identifying the patient's respiratory state based on the change in cross-correlation data includes: if the cross-correlation data is greater than zero, then the patient's respiratory state is determined to be assisted inspiration; if the cross-correlation data is less than zero, then the patient's respiratory state is determined to be assisted expiration.

[0144] It should be noted that, in the embodiments of the present invention, under normal circumstances, the respiratory flow rate is greater than zero during the inhalation phase and less than zero during the exhalation phase, while the airway pressure is greater than zero. Therefore, when the ventilation device assists the patient in inhalation, the cross-correlation data between the respiratory flow rate and the airway pressure is greater than zero, and the processing module 602 can determine that the patient's breathing state is assisted inhalation. When the ventilation device assists the patient in exhalation, the cross-correlation data between the respiratory flow rate and the airway pressure is less than zero, and the processing module 602 can determine that the patient's breathing state is assisted exhalation.

[0145] Specifically, in embodiments of the present invention, the patient's respiratory state includes assisted inhalation and / or assisted exhalation. If the gas flow rate is the delivery flow rate, the step of the processing module 602 in identifying the patient's respiratory state based on changes in cross-correlation data includes: if the cross-correlation data increases, the patient's respiratory state is determined to be assisted inhalation; if the cross-correlation data decreases, the patient's respiratory state is determined to be assisted exhalation.

[0146] It should be noted that, in the embodiments of the present invention, under normal circumstances, the airway flow rate is greater than zero and the airway pressure is also greater than zero. When the ventilation device assists the patient in inhalation, the airway flow rate can remain constant, while the airway pressure will gradually increase. Therefore, the cross-correlation data corresponding to the airway flow rate and the airway pressure will increase, and the patient's breathing state can be determined to be assisted inhalation. When the ventilation device assists the patient in exhalation, the airway flow rate will decrease and the airway pressure will also decrease. Therefore, the cross-correlation data corresponding to the airway flow rate and the airway pressure will decrease, and the patient's breathing state can be determined to be assisted exhalation.

[0147] It should be noted that, in the embodiments of the present invention, after the processing module 602 identifies the patient's breathing state as assisted inspiration or assisted expiration based on the changes in cross-correlation data, it can also compare whether the identified patient's breathing state matches the current ventilation mode of the ventilation device and output the comparison result.

[0148] For example, in an embodiment of the present invention, the processing module 602 identifies the patient's breathing state as assisted inhalation. If the current ventilation mode of the ventilation device is assisted inhalation mode, that is, the two match, the processing module 602 can output a comparison result: 1, which is used to characterize the comparison result of the match. If the current ventilation mode of the ventilation device is assisted exhalation mode, that is, the two do not match, the processing module 602 can output a comparison result: 0, which is used to characterize the comparison result of the mismatch.

[0149] For example, in an embodiment of the present invention, the processing module 602 identifies the patient's breathing state as assisted inspiration. If the current ventilation mode of the ventilation device is assisted inspiration mode, i.e., the two match, the processing module 602 can output a first control command to the controller of the ventilation device. The controller controls the corresponding indicator light to display green according to the first control command, which is used to indicate the comparison result of the match. If the current ventilation mode of the ventilation device is assisted expiration mode, i.e., the two do not match, the processing module 602 can output a second control command to the controller. The controller controls the corresponding indicator light to display red according to the second control command, which is used to indicate the comparison result of the mismatch.

[0150] It is understood that, in the embodiments of the present invention, the processing module 602 may identify that the patient's breathing state is assisted inhalation, while the current ventilation mode of the ventilation device is assisted exhalation, that is, the two do not match, indicating that there is a problem with the ventilation mode or that some problems have occurred during the ventilation process. Based on this comparison result, medical staff can perform corresponding processing and maintenance.

[0151] This invention provides a respiratory recognition method. During mechanical ventilation, airway pressure and gas flow rate are acquired; cross-correlation data corresponding to airway pressure and gas flow rate are determined based on the airway pressure and gas flow rate; and the patient's respiratory status is identified based on changes in the cross-correlation data. In other words, the technical solution provided by this invention can identify the patient's respiratory status based on changes in the cross-correlation data of airway pressure and gas flow rate during mechanical ventilation, thereby effectively reducing the impact of interference signals on respiratory recognition and improving the accuracy of respiratory recognition.

[0152] Another embodiment of the present invention provides a breathing recognition device. Figure 6 This is a schematic diagram of a breathing recognition device provided in an embodiment of the present invention. Figure 6 As shown, the device includes:

[0153] The acquisition module 601 acquires airway pressure and gas flow rate during mechanical ventilation; the gas flow rate is the respiratory flow rate or the delivery flow rate.

[0154] The processing module 602 determines the cross-correlation data corresponding to the airway pressure and the gas flow rate based on the airway pressure and the gas flow rate; and identifies whether spontaneous breathing occurs based on the changes in the cross-correlation data.

[0155] Optionally, the processing module 602 performs cross-correlation calculations on the airway pressure and the gas flow rate according to a preset signal sampling rate and a preset sampling time to obtain the cross-correlation data.

[0156] Optionally, the processing module 602 acquires a first sampled value corresponding to the airway pressure and a second sampled value corresponding to the gas flow rate within the preset sampling time according to the preset signal sampling rate; and performs cross-correlation calculation on the first sampled value and the second sampled value to obtain the cross-correlation data.

[0157] Optionally, the patient's respiratory status includes spontaneous inspiration and / or spontaneous expiration.

[0158] After the processing module 602 identifies the patient's respiratory status based on the changes in the cross-correlation data, it controls the ventilation device to switch ventilation modes according to the identified patient's respiratory status.

[0159] Optionally, the step of the processing module 602 controlling the ventilation device to switch ventilation modes according to the identified patient's respiratory status includes:

[0160] If the patient's breathing state changes from spontaneous exhalation to spontaneous inhalation, the ventilation device is triggered to enter the inspiratory ventilation mode;

[0161] If the patient's breathing state changes from spontaneous inhalation to spontaneous exhalation, the ventilation device is triggered to enter the expiratory ventilation mode.

[0162] Optionally, the gas flow rate is the respiratory flow rate, and the step of the processing module 602 identifying the patient's respiratory status based on the changes in the cross-correlation data includes:

[0163] If the cross-correlation data is greater than the first preset threshold, the patient's breathing state is determined to be spontaneous inhalation;

[0164] If the cross-correlation data is less than the second preset threshold, the patient's breathing state is determined to be spontaneous exhalation.

[0165] Optionally, the gas flow rate is the delivery gas flow rate, and the step of the processing module 602 identifying the patient's respiratory status based on the changes in the cross-correlation data includes:

[0166] Determine the parameter baseline corresponding to the cross-correlation data;

[0167] If the cross-correlation data is greater than the parameter baseline, and the difference between the cross-correlation data and the parameter baseline is greater than a third preset threshold, then the patient's breathing state is determined to be spontaneous exhalation.

[0168] If the cross-correlation data is less than the parameter baseline, and the difference between the cross-correlation data and the parameter baseline is greater than a fourth preset threshold, then the patient's breathing state is determined to be spontaneous inhalation.

[0169] Optionally, the step of the processing module 602 in determining the parameter baseline corresponding to the cross-correlation data includes:

[0170] Calculate the cross-correlation data within the first time period;

[0171] The cross-correlation data within the first time period is low-pass filtered to obtain the parameter baseline.

[0172] Optionally, the patient's respiratory state includes asphyxiation, and the step of the processing module 602 identifying the patient's respiratory state based on changes in the cross-correlation data includes:

[0173] If the fluctuation range of the cross-correlation data is less than a preset fluctuation range threshold, the patient's respiratory state is determined to be asphyxiation.

[0174] Optionally, the patient's respiratory status includes assisted inspiration and / or assisted expiration.

[0175] Optionally, after the processing module 602 identifies the patient's respiratory state based on the changes in the cross-correlation data, it compares whether the identified patient's respiratory state matches the current ventilation mode of the ventilation device and outputs the comparison result.

[0176] Optionally, the gas flow rate is the respiratory flow rate, and the step of the processing module 602 identifying the patient's respiratory status based on the changes in the cross-correlation data includes:

[0177] If the cross-correlation data is greater than zero, the patient's respiratory state is determined to be assisted inspiration;

[0178] If the cross-correlation data is less than zero, the patient's respiratory state is determined to be assisted exhalation.

[0179] Optionally, the gas flow rate is the delivery gas flow rate, and the step of the processing module 602 identifying the patient's respiratory status based on the changes in the cross-correlation data includes:

[0180] If the cross-correlation data increases, the patient's respiratory status is determined to be assisted inspiration;

[0181] If the cross-correlation data decreases, the patient's respiratory status is determined to be assisted exhalation.

[0182] This invention provides a respiratory recognition device that, during mechanical ventilation, acquires airway pressure and gas flow rate; determines cross-correlation data corresponding to airway pressure and gas flow rate based on the airway pressure and gas flow rate; and identifies the patient's respiratory status based on changes in the cross-correlation data. In other words, the respiratory recognition device provided by this invention can identify the patient's respiratory status during mechanical ventilation by analyzing changes in the cross-correlation data of airway pressure and gas flow rate, thereby effectively reducing the impact of interference signals on respiratory recognition and improving the accuracy of respiratory recognition.

[0183] This invention provides a ventilation device. Figure 7 This is a schematic diagram of a ventilation device provided in an embodiment of the present invention. Figure 7 As shown, the ventilation device includes the above-mentioned breathing recognition device 701, and also includes: a gas source 702, a breathing tubing 703, a display 704, and a controller 705;

[0184] The gas source 702 provides gas during mechanical ventilation;

[0185] The breathing tubing 703 is connected to the air source 702, providing inhalation and exhalation pathways during the mechanical ventilation process;

[0186] The breathing recognition device 701 is connected to the breathing tubing 703 and the controller 705;

[0187] The respiratory recognition device 701 identifies the patient's respiratory status during the mechanical ventilation process;

[0188] The controller 705 is also connected to the air source 702 to control the mechanical ventilation process;

[0189] The display 704 is connected to the controller 705 and displays the respiratory waveform during the mechanical ventilation process.

[0190] This invention provides a computer-readable storage medium storing a breathing recognition program, which can be executed by a processor to implement the breathing recognition method described above. The computer-readable storage medium can be volatile memory, such as random-access memory (RAM); or non-volatile memory, such as read-only memory (ROM), flash memory, hard disk drive (HDD), or solid-state drive (SSD); or it can be a device including one or any combination of the above-mentioned memories, such as a mobile phone, computer, tablet device, personal digital assistant, etc.

[0191] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of hardware embodiments, software embodiments, or embodiments combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage and optical storage) containing computer-usable program code.

[0192] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable signal processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable signal processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0193] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable signal processing device to operate in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0194] These computer program instructions can also be loaded onto a computer or other programmable signal processing device to cause a series of operational steps to be performed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable device for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0195] The above description is merely a preferred embodiment of the present invention and is not intended to limit the scope of protection of the present invention.

[0196] Industrial applicability

[0197] In the technical solution of this invention embodiment, during mechanical ventilation, airway pressure and gas flow rate are acquired; based on the airway pressure and gas flow rate, cross-correlation data corresponding to the airway pressure and gas flow rate are determined; and the patient's respiratory status is identified based on changes in the cross-correlation data. In other words, the technical solution provided by this invention embodiment can identify the patient's respiratory status based on changes in the cross-correlation data of airway pressure and gas flow rate during mechanical ventilation, thereby effectively reducing the impact of interference signals on respiratory recognition and improving the accuracy of respiratory recognition.

Claims

1. A respiratory recognition method, applied to a ventilation device, characterized in that, The method includes: During mechanical ventilation, airway pressure and gas flow rate are measured. Cross-correlation calculations are performed on the airway pressure and the gas flow rate at the same time to determine the cross-correlation data corresponding to the airway pressure and the gas flow rate; The patient's respiratory status is identified based on changes in the cross-correlation data.

2. The method according to claim 1, characterized in that, The step of determining the cross-correlation data corresponding to the airway pressure and the gas flow rate based on the airway pressure and the gas flow rate includes: According to the preset signal sampling rate and preset sampling time, the cross-correlation calculation is performed on the airway pressure and the gas flow rate to obtain the cross-correlation data.

3. The method according to claim 2, characterized in that, The step of performing cross-correlation calculations on the airway pressure and the gas flow rate according to a preset signal sampling rate and a preset sampling time to obtain the cross-correlation data includes: Based on the preset signal sampling rate, the first sampling value corresponding to the airway pressure and the second sampling value corresponding to the gas flow rate are obtained within the preset sampling time. The cross-correlation data is obtained by performing cross-correlation calculations on the first sampled value and the second sampled value.

4. The method according to claim 1, characterized in that, The cross-correlation between the airway pressure and the gas flow rate is calculated using the following formula to determine the cross-correlation data between the airway pressure and the gas flow rate: in, Corr(k) This represents the cross-correlation data between airway pressure and gas flow rate at time k. Flow(i) This represents the gas flow rate at time i. Pressure(i) This represents the airway pressure at time i.

5. The method according to claim 1, characterized in that, The patient's respiratory status includes spontaneous inspiration and / or spontaneous expiration. After identifying the patient's respiratory status based on changes in the cross-correlation data, the method further includes: The ventilation device is controlled to switch ventilation modes based on the identified patient's respiratory status.

6. The method according to claim 5, characterized in that, The step of controlling the ventilation device to switch ventilation modes based on the identified patient's respiratory status includes: If the patient's breathing state changes from spontaneous exhalation to spontaneous inhalation, the ventilation device is triggered to enter the inspiratory ventilation mode; If the patient's breathing state changes from spontaneous inhalation to spontaneous exhalation, the ventilation device is triggered to enter the expiratory ventilation mode.

7. The method according to claim 5, characterized in that, The gas flow rate is the respiratory flow rate, and the step of identifying the patient's respiratory status based on changes in the cross-correlation data includes: If the cross-correlation data is greater than the first preset threshold, the patient's breathing state is determined to be spontaneous inhalation; If the cross-correlation data is less than the second preset threshold, the patient's breathing state is determined to be spontaneous exhalation.

8. The method according to claim 5, characterized in that, The gas flow rate is the delivery gas flow rate, and the step of identifying the patient's respiratory status based on changes in the cross-correlation data includes: Determine the parameter baseline corresponding to the cross-correlation data; If the cross-correlation data is greater than the parameter baseline, and the difference between the cross-correlation data and the parameter baseline is greater than a third preset threshold, then the patient's breathing state is determined to be spontaneous exhalation. If the cross-correlation data is less than the parameter baseline, and the difference between the cross-correlation data and the parameter baseline is greater than a fourth preset threshold, then the patient's breathing state is determined to be spontaneous inhalation.

9. The method according to claim 8, characterized in that, The step of determining the parameter baseline corresponding to the cross-correlation data includes: Calculate the cross-correlation data within the first time period; The cross-correlation data within the first time period is low-pass filtered to obtain the parameter baseline.

10. The method according to claim 1, characterized in that, The patient's respiratory status includes asphyxia, and the step of identifying the patient's respiratory status based on changes in the cross-correlation data includes: If the fluctuation range of the cross-correlation data is less than a preset fluctuation range threshold, the patient's respiratory state is determined to be asphyxiation.

11. The method according to claim 1, characterized in that, The patient's respiratory status includes assisted inspiration and / or assisted expiration.

12. The method according to claim 11, characterized in that, After identifying the patient's respiratory status based on changes in the cross-correlation data, the method further includes: The system compares whether the identified patient's respiratory status matches the current ventilation mode of the ventilation device and outputs the comparison result.

13. The method according to claim 11, characterized in that, The gas flow rate is the respiratory flow rate, and the step of identifying the patient's respiratory status based on changes in the cross-correlation data includes: If the cross-correlation data is greater than zero, the patient's respiratory state is determined to be assisted inspiration; If the cross-correlation data is less than zero, the patient's respiratory state is determined to be assisted exhalation.

14. The method according to claim 11, characterized in that, The gas flow rate is the delivery gas flow rate, and the step of identifying the patient's respiratory status based on changes in the cross-correlation data includes: If the cross-correlation data increases, the patient's respiratory status is determined to be assisted inspiration; If the cross-correlation data decreases, the patient's respiratory status is determined to be assisted exhalation.

15. A ventilation device, characterized in that, Includes a gas source, breathing tubing, display, controller, and breathing recognition device; The gas source provides gas during mechanical ventilation; The breathing tubing is connected to the air source and provides inhalation and exhalation pathways during the mechanical ventilation process; The breathing recognition device is connected to the breathing tubing and the controller; The respiratory recognition device is used to perform the respiratory recognition method according to any one of claims 1-14 to identify the patient's respiratory status during the mechanical ventilation. The controller is also connected to the air source to control the mechanical ventilation process; The display is connected to the controller and displays the respiratory waveform during mechanical ventilation.

16. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a breathing recognition program, which can be executed by a processor to implement the breathing recognition method according to any one of claims 1-14.

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