Method for detecting pulmonary function parameters and anesthetic machine

Abstract

The present application provides a method for detecting pulmonary function parameters and an anesthesia machine. The method includes: collecting the breathing parameters of a user; the breathing parameters include expiratory pressure data, expiratory time data, and tidal volume; based on the breathing parameters, determining the leakage coefficient of the breathing circuit system corresponding to the user; according to the leakage coefficient, expiratory pressure data, and expiratory time data, determining the expiratory phase time parameter of the user; according to the leakage coefficient and the expiratory phase time parameter, determining the pulmonary function parameter of the user. In the present application, the leakage coefficient of the breathing circuit system corresponding to the user is determined through the expiratory parameters, and then the expiratory phase time parameter corresponding to the user is determined. In this way, the gas leakage amount of the anesthesia machine can be quantitatively processed. Finally, the pulmonary function parameter of the user is calculated according to the leakage coefficient and the expiratory phase time parameter, avoiding the influence of the gas leakage amount on the calculation of the pulmonary function parameter and improving the accuracy of the detection of the pulmonary function parameter.

Description

Technical Field

[0001] The present application relates to the field, and in particular to a method for detecting pulmonary function parameters and an anesthesia machine. Background Art

[0002] An anesthesia machine is one of the key devices to ensure the safety of patients and the success of surgeries. The anesthesia machine helps the patient remain pain-free and unconscious during the surgery by providing an appropriate amount of anesthetic gas and oxygen. During the process of ventilating the patient using the anesthesia machine, the anesthesia machine usually needs to detect the pulmonary function parameters of the patient to reflect the actual ventilation situation of the patient.

[0003] In the related art, when determining the pulmonary function parameters, the anesthesia machine usually detects and calculates the pulmonary function parameters based on the expiratory pressure and flow data by means of the least squares method, etc. However, due to the existence of a certain amount of gas leakage in the anesthesia machine, the accuracy of this pulmonary function detection method in the related art is not high. Summary of the Invention

[0004] The present application provides a method for detecting pulmonary function parameters and an anesthesia machine, which improves the accuracy of detecting pulmonary function parameters.

[0005] In a first aspect, an embodiment of the present application provides a method for detecting pulmonary function parameters, including:

[0006] Collecting the respiratory parameters of the user; the respiratory parameters include expiratory pressure data, expiratory time data, and respiratory tidal volume;

[0007] Based on the respiratory parameters, determining the leakage coefficient of the respiratory circuit system corresponding to the user;

[0008] According to the leakage coefficient, the expiratory pressure data, and the expiratory time data, determining the expiratory phase time parameter of the user;

[0009] According to the leakage coefficient and the expiratory phase time parameter, determining the pulmonary function parameters of the user.

[0010] In a possible implementation manner, the collecting the respiratory parameters of the user includes:

[0011] According to the change situation of the respiratory flow rate, determining the expiratory start pressure and the expiratory start moment, and opening the expiratory valve of the anesthesia machine;

[0012] During the process of the expiratory pressure decreasing, recording the expiratory moment and the expiratory pressure value corresponding to the expiratory moment within each preset sampling period according to the preset sampling period;

[0013] When the expiratory pressure drops to a preset pressure value, perform closed-loop control on the expiratory valve and stop recording the expiratory moment and the expiratory pressure value to obtain the expiratory pressure data and the expiratory time data.

[0014] In a possible implementation manner, the collecting the respiratory parameters of the user includes:

[0015] Determine the end-inspiration moment and the end-expiration moment corresponding to the user according to the change of the respiratory flow rate;

[0016] Calculate the inspiratory tidal volume at the end-inspiration moment according to the inspiratory flow rate during the inspiratory process, and calculate the expiratory tidal volume at the end-expiration moment according to the expiratory flow rate during the expiratory process to obtain the respiratory tidal volume of the user.

[0017] In a possible implementation manner, the determining the leakage coefficient of the respiratory circuit system corresponding to the user based on the respiratory parameters includes:

[0018] Determine the gas leakage amount of the user according to the difference between the inspiratory tidal volume and the expiratory tidal volume in the respiratory tidal volume;

[0019] Determine the expiratory pressure cumulative data corresponding to the user according to the expiratory pressure data and the expiratory time data;

[0020] Determine the leakage coefficient based on the gas leakage amount and the expiratory pressure cumulative data.

[0021] In a possible implementation manner, the expiratory phase time parameters include an expiratory phase comprehensive time constant, an expiratory phase additional time constant, and an expiratory phase physiological time constant; the determining the expiratory phase time parameters of the user according to the leakage coefficient, the expiratory pressure data, and the expiratory time data includes:

[0022] Determine the target correlation relationship among the expiratory phase comprehensive time constant, the expiratory phase additional time constant, and the expiratory phase physiological time constant according to the leakage coefficient;

[0023] Determine the expiratory phase time parameters of the user according to the expiratory pressure data, the expiratory time data, and the target correlation relationship.

[0024] In a possible implementation manner, the determining the target correlation relationship among the expiratory phase comprehensive time constant, the expiratory phase additional time constant, and the expiratory phase physiological time constant includes:

[0025] Determine the target correlation relationship according to the target pressure model corresponding to the anesthesia machine through the pressure relationship in the target pressure model;

[0026] Among them, the target pressure model includes a constant pressure source, a loop pressure, an analog capacitor, an analog resistor, and a leakage gas resistance; the analog capacitor and the analog resistor correspond to the lung function parameters.

[0027] In a possible implementation manner, the determining of the expiratory phase time parameter of the user according to the expiratory pressure data, the expiratory time data, and the target correlation relationship includes:

[0028] Determine an exponential decay function corresponding to the expiratory pressure drop process, and according to the exponential decay function, determine the correlation relationship between the comprehensive expiratory time constant, the expiratory pressure value, and the expiratory moment;

[0029] Determine the comprehensive expiratory time constant according to the expiratory pressure data, the expiratory time data, and the correlation relationship;

[0030] Determine the additional expiratory time constant and the physiological expiratory time constant according to the expiratory pressure data, the expiratory time data, the comprehensive expiratory time constant, and the target correlation relationship.

[0031] In a possible implementation manner, the lung function parameter includes at least one of expiratory compliance and expiratory gas resistance; the determining of the lung function parameter of the user according to the leakage coefficient and the expiratory phase time parameter includes:

[0032] Determine the expiratory compliance according to the leakage coefficient and the additional expiratory time constant;

[0033] Determine the expiratory gas resistance based on the physiological expiratory time constant and the expiratory compliance.

[0034] In a possible implementation manner, the method further includes:

[0035] During the current breathing process, display the lung function parameters of the user during the previous breathing process on the display screen.

[0036] In a second aspect, an embodiment of the present application provides a lung function parameter detection device, including:

[0037] An acquisition module, configured to acquire the breathing parameters of the user; the breathing parameters include expiratory pressure data, expiratory time data, and breathing tidal volume;

[0038] A first determination module, configured to determine the leakage coefficient of the breathing circuit system corresponding to the user based on the breathing parameters;

[0039] A second determination module, configured to determine an expiratory phase time parameter of the user according to the leakage coefficient, the expiratory pressure data, and the expiratory time data;

[0040] A third determination module, configured to determine a lung function parameter of the user according to the leakage coefficient and the expiratory phase time parameter.

[0041] In a possible implementation manner, the acquisition module is specifically configured to:

[0042] Determine an expiratory start pressure and an expiratory start moment according to a change in respiratory flow rate, and open an expiratory valve of an anesthesia machine;

[0043] During a process of decreasing expiratory pressure, record an expiratory moment and an expiratory pressure value corresponding to the expiratory moment within each preset sampling period according to a preset sampling period;

[0044] When the expiratory pressure drops to a preset pressure value, perform closed-loop control on the expiratory valve, and stop recording the expiratory moment and the expiratory pressure value, so as to obtain the expiratory pressure data and the expiratory time data.

[0045] In a possible implementation manner, the acquisition module is specifically configured to:

[0046] Determine an end-inspiratory moment and an end-expiratory moment corresponding to the user according to a change in respiratory flow rate;

[0047] Calculate an inspiratory tidal volume at the end-inspiratory moment according to an inspiratory flow rate during an inspiratory process, and calculate an expiratory tidal volume at the end-expiratory moment according to an expiratory flow rate during an expiratory process, so as to obtain a respiratory tidal volume of the user.

[0048] In a possible implementation manner, the first determination module is specifically configured to:

[0049] Determine a gas leakage amount of the user according to a difference between an inspiratory tidal volume and an expiratory tidal volume in the respiratory tidal volume;

[0050] Determine an expiratory pressure cumulative data corresponding to the user according to the expiratory pressure data and the expiratory time data;

[0051] Determine the leakage coefficient based on the gas leakage amount and the expiratory pressure cumulative data.

[0052] In a possible implementation manner, the expiratory phase time parameter includes an expiratory phase comprehensive time constant, an expiratory phase additional time constant, and an expiratory phase physiological time constant; the second determination module is specifically configured to:

[0053] Determine the target correlation relationship among the expiratory phase comprehensive time constant, the expiratory phase additional time constant, and the expiratory phase physiological time constant according to the leakage coefficient;

[0054] Determine the expiratory phase time parameter of the user according to the expiratory pressure data, the expiratory time data, and the target correlation relationship.

[0055] In a possible implementation manner, the second determination module is specifically configured to:

[0056] Determine the target correlation relationship according to the target pressure model corresponding to the anesthesia machine through the pressure relationship in the target pressure model;

[0057] Wherein, the target pressure model includes a constant pressure source, a circuit pressure, an analog capacitor, an analog resistor, and a leakage air resistance; the analog capacitor and the analog resistor correspond to the lung function parameters.

[0058] In a possible implementation manner, the second determination module is specifically configured to:

[0059] Determine the exponential decay function corresponding to the expiratory pressure drop process, and determine the correlation relationship between the expiratory phase comprehensive time constant, the expiratory pressure value, and the expiratory time according to the exponential decay function;

[0060] Determine the expiratory phase comprehensive time constant according to the expiratory pressure data, the expiratory time data, and the correlation relationship;

[0061] Determine the expiratory phase additional time constant and the expiratory phase physiological time constant according to the expiratory pressure data, the expiratory time data, the expiratory phase comprehensive time constant, and the target correlation relationship.

[0062] In a possible implementation manner, the lung function parameters include at least one of the expiratory phase compliance and the expiratory phase air resistance; the third determination module is specifically configured to:

[0063] Determine the expiratory phase compliance according to the leakage coefficient and the expiratory phase additional time constant;

[0064] Determine the expiratory phase air resistance based on the expiratory phase physiological time constant and the expiratory phase compliance.

[0065] In a possible implementation manner, the device is further configured to:

[0066] During the current breathing process, display the lung function parameters of the user during the previous breathing process on the display screen.

[0067] In a third aspect, an embodiment of the present application provides a pulmonary function parameter detection device, including: a processor and a memory;

[0068] The memory stores computer-executable instructions;

[0069] The processor executes the computer-executable instructions stored in the memory to implement the pulmonary function parameter detection method according to any one of the first aspects.

[0070] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, in which computer-executable instructions are stored, and when the computer-executable instructions are executed, they are used to implement the pulmonary function parameter detection method according to any one of the first aspects.

[0071] In a fifth aspect, an embodiment of the present application provides a computer program product, including a computer program, and when the computer program is executed, it implements the pulmonary function parameter detection method according to any one of the first aspects.

[0072] In a sixth aspect, an embodiment of the present application provides an anesthesia machine, and the anesthesia machine can implement the pulmonary function parameter detection method according to any one of the first aspects.

[0073] The pulmonary function parameter detection method and anesthesia machine provided by the embodiments of the present application collect the breathing parameters of the user; the breathing parameters include expiratory pressure data, expiratory time data, and tidal volume; based on the breathing parameters, the leakage coefficient of the breathing circuit system corresponding to the user is determined; according to the leakage coefficient, expiratory pressure data, and expiratory time data, the expiratory phase time parameter of the user is determined; according to the leakage coefficient and the expiratory phase time parameter, the pulmonary function parameter of the user is determined. In the present application, the leakage coefficient of the breathing circuit system corresponding to the user is determined through the expiratory parameters, and then the expiratory phase time parameter corresponding to the user is determined, so that the gas leakage amount of the anesthesia machine can be quantified, and finally the pulmonary function parameter of the user is calculated according to the leakage coefficient and the expiratory phase time parameter, avoiding the influence of the gas leakage amount on the calculation of the pulmonary function parameter and improving the accuracy of the pulmonary function parameter detection. BRIEF DESCRIPTION OF THE DRAWINGS

[0074] Figure 1 is a schematic diagram of an application scenario provided by an embodiment of the present application;

[0075] Figure 2 is a schematic flowchart of a pulmonary function parameter detection method provided by an embodiment of the present application;

[0076] Figure 3 is a schematic flowchart of the breathing parameter acquisition process provided by an embodiment of the present application;

[0077] Figure 4Schematic flowchart of another method for detecting pulmonary function parameters provided by an embodiment of the present application;

[0078] Figure 5 Schematic diagram of a target pressure model provided by an embodiment of the present application;

[0079] Figure 6 Logical schematic diagram of pulmonary function parameter detection provided by an embodiment of the present application;

[0080] Figure 7 Schematic structural diagram of a pulmonary function parameter detection device provided by an embodiment of the present application;

[0081] Figure 8 Schematic structural diagram of a pulmonary function parameter detection device provided by an embodiment of the present application. Detailed implementation manners

[0082] To enable those skilled in the art to better understand the technical solutions of the present application, the present application will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments and drawings described herein are only used to explain the present application, rather than to limit the present application. It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data for analysis, stored data, displayed data, etc.) involved in the present application are all information and data authorized by the user or fully authorized by all parties, and the collection, use, and processing of relevant data need to comply with relevant laws, regulations, and standards, and corresponding operation entrances are provided for the user to select authorization or refusal.

[0083] During the process of a patient (or user) using an anesthesia machine for ventilation, the anesthesia machine usually needs to monitor the pulmonary function parameters of the patient. The pulmonary function parameters may specifically include expiratory compliance and expiratory airway resistance, etc. Among them, the detection of respiratory compliance is to calculate the compliance of the patient's lungs during the exhalation phase, which is used to evaluate the elasticity of the patient's lungs during exhalation in the treatment process. This compliance is the change in volume corresponding to a unit pressure, and its calculation formula is C = ΔV / ΔP, where the volume change value ΔV is in milliliters (ml), the pressure change value ΔP is in centimeters of water column (cmH2O), and the compliance C is in milliliters per centimeter of water column (ml / cmH2O). The expiratory airway resistance is the airway resistance of the patient during the exhalation phase, which is used to evaluate whether the patient's airway is blocked, and the unit is centimeters of water column per liter per minute (cmH2O / L / min).

[0084] In the related art, during the ventilation process of an anesthesia machine, the expiratory pressure and flow rate data are usually used to calculate the patient's pulmonary function parameters by means of the least squares method or the like. However, since there is usually a certain amount of gas leakage in the anesthesia machine, this method of detecting pulmonary function parameters in the related art cannot eliminate the influence of the gas leakage amount on the calculation of pulmonary function parameters, resulting in low accuracy of the detection of pulmonary function parameters.

[0085] To solve the above problems, an embodiment of the present application provides a method for detecting pulmonary function parameters and an anesthesia machine. The anesthesia machine collects the user's breathing parameters, which include expiratory pressure data, expiratory time data, and tidal volume. Then, according to the breathing parameters, the leakage coefficient of the user's corresponding breathing circuit system is determined. Then, based on the leakage coefficient, expiratory pressure data, and expiratory time data, the expiratory phase time parameter of the user is calculated. Finally, the user's pulmonary function parameters are calculated based on the leakage coefficient and the expiratory phase time parameter. In this way, when calculating the pulmonary function parameters, the anesthesia machine can quantify the gas leakage amount according to the leakage coefficient and the expiratory phase time parameter, fully consider the influence of gas leakage, and can effectively eliminate the influence of the leakage amount on the calculation of pulmonary function parameters, improving the accuracy of the detection of pulmonary function parameters.

[0086] Figure 1 FIG. is a schematic diagram of an application scenario provided by an embodiment of the present application. As Figure 1 shown, in the related art, the anesthesia machine 101 usually calculates the pulmonary function parameters by the least squares method for the user's expiratory pressure and flow rate data. This method of calculating pulmonary function parameters is easily affected by the gas leakage amount of the anesthesia machine, resulting in inaccurate detection results.

[0087] In the embodiment of the present application, the anesthesia machine 101 quantifies the gas leakage amount according to the user's breathing parameters, obtains the leakage coefficient of the user's corresponding breathing circuit system and the expiratory phase time parameter, and then determines the user's pulmonary function parameters according to the leakage coefficient and the expiratory phase time parameter. In this way, by quantifying the gas leakage amount, the anesthesia machine 101 can eliminate the influence of the gas leakage amount on the calculation of pulmonary function parameters and improve the accuracy of the detection of pulmonary function parameters.

[0088] The following details the solution shown in the present application through specific embodiments. It should be noted that the following several embodiments can exist independently or be combined with each other, and the same or similar content will not be repeated in different embodiments.

[0089] Figure 2 FIG. is a schematic flowchart of a method for detecting pulmonary function parameters provided by an embodiment of the present application. Please refer to Figure 2 and the method for detecting pulmonary function parameters may include:

[0090] S201. Collect the user's breathing parameters, which include expiratory pressure data, expiratory time data, and tidal volume.

[0091] The execution entity of the embodiment of the present application can be an anesthesia machine or a pulmonary function parameter detection device set in the anesthesia machine. The pulmonary function parameter detection device can be implemented by software or by a combination of software and hardware. For the convenience of understanding, in the following, the anesthesia machine is taken as an example of the execution entity for illustration.

[0092] In the embodiment of the present application, the user can refer to the user of the anesthesia machine, also known as the patient, etc. The breathing parameters can refer to various breathing parameters corresponding to the user, specifically including expiratory pressure data, expiratory time data, and tidal volume, etc. Among them, the expiratory time data can refer to the time series when the user exhales using the anesthesia machine, which can include different expiratory moments. The expiratory pressure data can refer to the expiratory pressure series when the user exhales using the anesthesia machine, which can include the expiratory pressure values corresponding to different expiratory moments, and can be specifically detected by a pressure sensor. The tidal volume can refer to the expiratory tidal volume and inspiratory tidal volume of the user, which can refer to the volume of gas inhaled or exhaled each time when the user breathes calmly. The anesthesia machine can specifically collect the expiratory flow rate and inspiratory flow rate through a flow sensor, and calculate the tidal volume based on the expiratory flow rate and inspiratory flow rate. Of course, other collection methods can also be used, and the embodiment of the present application does not limit this.

[0093] In this step, the anesthesia machine can collect the user's breathing parameters through detection devices such as a flow sensor and a pressure sensor to obtain the user's expiratory pressure data, expiratory time data, and tidal volume, and subsequent pulmonary function parameters of the user can be calculated based on these breathing parameters. Of course, other collection devices or other collection methods can also be used by the anesthesia machine during the data collection process, and can be specifically set flexibly based on actual needs. The embodiment of the present application does not limit this.

[0094] S202. Determine the leakage coefficient of the breathing circuit system corresponding to the user based on the breathing parameters.

[0095] In the embodiments of the present application, the leakage coefficient may refer to the linear relationship coefficient between the leakage flow rate of the leakage port in the breathing circuit system composed of the anesthesia machine and the user and the pressure during the exhalation phase, and can be used to characterize the speed of gas leakage in the breathing circuit system during the user's exhalation process. Specifically, after the anesthesia machine collects the user's breathing parameters, it can first determine the gas leakage amount during the exhalation process based on the tidal volume in the breathing parameters, and then calculate the leakage coefficient of the user's corresponding breathing circuit system through the gas leakage amount, the exhalation pressure data and the exhalation time data in the breathing parameters, so as to realize the quantification of gas leakage during the user's exhalation process and improve the accuracy of subsequent calculation of lung function parameters.

[0096] S203. Determine the exhalation phase time parameter of the user according to the leakage coefficient, the exhalation pressure data and the exhalation time data.

[0097] In the embodiments of the present application, the time parameter can be used to characterize the change speed of the flow rate of the user's lungs under the action of power and resistance, that is, the speed of lung filling and emptying. The exhalation phase time parameter refers to the time parameter during the user's exhalation process. In a possible implementation manner, the exhalation phase time parameter may specifically include an exhalation phase comprehensive time constant, an exhalation phase additional time constant, and an exhalation phase physiological time constant. Among them, the respiratory phase physiological time constant may refer to the physiological time constant during the normal exhalation process of the user's lungs. The exhalation phase additional time constant may refer to an additional time constant caused by the gas leakage of the anesthesia machine. The exhalation phase comprehensive time constant may refer to the time constant actually shown during the user's exhalation process when using the anesthesia machine, and may refer to the actual characteristics shown after the joint action of the exhalation phase additional time constant and the respiratory phase physiological time constant.

[0098] In this step, after the anesthesia machine calculates the leakage coefficient of the user's corresponding breathing circuit system, it can further calculate the exhalation phase time parameter of the user according to the leakage coefficient, the exhalation pressure data and the exhalation time data in the breathing parameters. Specifically, the anesthesia machine can first determine the target correlation relationship between the time constants in the exhalation phase time parameter according to the leakage coefficient, and then calculate the exhalation phase time parameter through the target correlation relationship, the user's exhalation pressure data and the exhalation time data. The target correlation relationship can be used to characterize the mutual influence relationship between the time constants. In this way, the anesthesia machine determines the exhalation time parameter during the user's exhalation process according to the leakage coefficient, the exhalation pressure data and the exhalation time data, which can realize the quantification process based on the gas leakage amount, eliminate the influence of gas leakage on the detection of lung function parameters, and improve the accuracy of the detection of lung function parameters.

[0099] S204. Determine the lung function parameter of the user according to the leakage coefficient and the exhalation phase time parameter.

[0100] In the embodiments of the present application, the pulmonary function parameter may refer to the breathing parameter corresponding to the user, specifically including expiratory compliance, expiratory airway resistance, etc. After the anesthetic machine determines the leakage coefficient and the expiratory phase time parameter, the pulmonary function parameter can be calculated according to the leakage coefficient and the respiratory phase time parameter.

[0101] For the pulmonary function parameter detection method provided by the embodiments of the present application, the anesthetic machine collects the breathing parameters of the user; the breathing parameters include expiratory pressure data, expiratory time data, and respiratory tidal volume; based on the breathing parameters, the leakage coefficient of the breathing circuit system corresponding to the user is determined; according to the leakage coefficient, expiratory pressure data, and expiratory time data, the expiratory phase time parameter of the user is determined; according to the leakage coefficient and the expiratory phase time parameter, the pulmonary function parameter of the user is determined. In the present application, the leakage coefficient of the breathing circuit system corresponding to the user is determined through the expiratory parameters, and then the expiratory phase time parameter corresponding to the user is determined, so that the gas leakage amount of the anesthetic machine can be quantified, and finally the pulmonary function parameter of the user is calculated according to the leakage coefficient and the expiratory phase time parameter, avoiding the influence of the gas leakage amount on the calculation of the pulmonary function parameter and improving the accuracy of the pulmonary function parameter detection.

[0102] Based on the above embodiments, Figure 3 is a schematic flowchart of the breathing parameter acquisition process provided by the embodiments of the present application. Please refer to Figure 3 and the breathing parameter acquisition process may specifically include:

[0103] S301. Determine the expiratory start pressure and the expiratory start time according to the change of the breathing flow rate, and open the expiratory valve of the anesthetic machine.

[0104] In the embodiments of the present application, the expiratory start time may refer to the time corresponding to when the user starts to exhale, which can be represented by t0. The expiratory start pressure may refer to the expiratory pressure corresponding to the expiratory start time, which can be represented by P0. The expiratory valve may refer to the airflow direction control valve in the anesthetic machine, which can be used to control the airflow direction when the user exhales to ensure the smooth breathing of the user.

[0105] The change of the breathing flow rate may refer to the change of the direction of the user's expiratory flow rate. During the breathing process of the user, the anesthetic machine can detect the positive flow rate (the user inhales) and the negative flow rate (the user exhales) of the user with respect to the anesthetic machine. When there is a positive-negative direction switch in the flow rate, the anesthetic machine can determine that there is a conversion between exhalation and inhalation of the user.

[0106] Exemplarily, when the respiratory flow rate detected by the anesthesia machine changes from positive to negative, the anesthesia machine can determine that the user starts to exhale. At this time, the current moment and the current pressure can be recorded as the exhalation start moment and the exhalation start pressure. Meanwhile, the anesthesia machine can adjust the opening and closing state of the exhalation valve. For example, it can open the exhalation valve to release the pressure in the user's airway, ensuring that the user can exhale the gas in the respiratory system during the exhalation phase.

[0107] S302. During the process of the exhalation pressure dropping, record the exhalation moment and the corresponding exhalation pressure value within each preset sampling period according to the preset sampling period.

[0108] In the embodiments of the present application, the preset sampling period may refer to a pre-set data sampling time period. For example, it may refer to 1 millisecond, 5 milliseconds, or 10 milliseconds, etc. The exhalation moment may refer to different time points during the user's exhalation process. The exhalation pressure value may refer to the exhalation pressure corresponding to the user at different exhalation moments.

[0109] Specifically, after the anesthesia machine opens the exhalation valve, the exhalation pressure begins to gradually drop. The anesthesia machine can record an exhalation moment t at each preset time period according to the preset sampling period, for example, starting from the exhalation start moment t0. k and the corresponding exhalation pressure value P(t k ), where k can be a positive integer.

[0110] S303. When the exhalation pressure drops to the preset pressure value, perform closed-loop control on the exhalation valve and stop recording the exhalation moment and the exhalation pressure value to obtain the exhalation pressure data and the exhalation time data.

[0111] In the embodiments of the present application, the preset pressure value may refer to a pre-set pressure set value P set . During the user's exhalation process, since the pressure in the lungs of the body is higher than the external pressure, the exhalation pressure gradually decreases during exhalation. However, to ensure that there is a certain degree of inflation in the pulmonary alveoli, a preset pressure value can be pre-set in the anesthesia machine. When the exhalation pressure drops to the preset pressure value, the anesthesia machine can perform closed-loop control on the exhalation valve to ensure that the exhalation pressure no longer drops, avoiding negative impacts on the user's health. Specifically, the controller in this closed-loop control process can be a proportional-integral-derivative (PID) controller, which dynamically adjusts the opening and closing state (or opening degree, etc.) of the exhalation valve based on the difference between the actual exhalation pressure and the preset pressure value. Of course, other closed-loop control methods can also be used, and the embodiments of the present application do not limit this.

[0112] In this step, when the expiratory pressure of the anesthesia machine drops to a preset pressure value, the anesthesia machine can perform closed-loop control on the expiratory valve to ensure that the expiratory pressure no longer drops. At the same time, it can stop recording the expiratory moment and the expiratory pressure value, and obtain the expiratory pressure data and expiratory time data during the user's current exhalation process. Exemplarily, the expiratory pressure sequence corresponding to the expiratory pressure data can be expressed as [P0, P1, …, P n , and the expiratory time sequence corresponding to the expiratory time data can be expressed as [t0, t1, …, t n , where n is a positive integer.

[0113] In this way, during the user's exhalation process, the anesthesia machine records the expiratory pressure values at different expiratory moments of the user. At the same time, when the expiratory pressure drops to the preset pressure value, it stops data collection and performs closed-loop control on the expiratory valve, which can not only ensure the comprehensiveness and accuracy of data collection, but also ensure the smooth exhalation of the user and avoid negative impacts on the user.

[0114] S304. Determine the end-inspiration moment and end-expiration moment corresponding to the user according to the change of the respiratory flow rate.

[0115] S305. Calculate the inspiratory tidal volume at the end-inspiration moment according to the inspiratory flow rate during the inspiration process, and calculate the expiratory tidal volume at the end-expiration moment according to the expiratory flow rate during the exhalation process, to obtain the respiratory tidal volume of the user.

[0116] In the embodiment of the present application, the end-inspiration moment may be the last moment corresponding to the user's inspiration process. The end-expiration moment may refer to the last moment corresponding to the user's exhalation process. The end-expiration moment and the end-inspiration moment can be determined according to the change of the respiratory flow rate, and specifically can be determined based on the moment of the positive and negative direction change of the respiratory flow rate. Exemplarily, when the respiratory flow rate detected by the anesthesia machine changes from negative to positive, the anesthesia machine can determine that the user's exhalation process ends at this time and the inspiration process starts, and the anesthesia machine can use this moment as the end-expiration moment; when the respiratory flow rate detected by the anesthesia machine changes from positive to negative, the anesthesia machine can determine that the user's inspiration process ends and the exhalation process starts, and the anesthesia machine can use this moment as the end-inspiration moment.

[0117] The inspiratory tidal volume may refer to the volume of gas inhaled by the user during a single inspiration. The expiratory tidal volume may refer to the volume of gas exhaled by the user during a single exhalation. Among them, the inspiratory tidal volume can be obtained by integrating the detection values (inspiratory flow rate values at different moments) of the flow sensor during the user's inspiration phase (from the end-expiration moment to the end-inspiration moment), and can be expressed as V insp ; the expiratory tidal volume can be obtained by integrating the detection values (expiratory flow rate values at different moments) of the flow sensor during the user's exhalation phase (from the end-inspiration moment to the end-expiration moment), and specifically can be expressed as V expOf course, the anesthesia machine can also measure the expiratory tidal volume and inspiratory tidal volume by other means, and the embodiments of the present application do not limit this.

[0118] In the embodiments of the present application, the anesthesia machine determines the end-inspiration moment and end-expiration moment of the user according to the change of the respiratory flow rate, and then calculates the expiratory tidal volume corresponding to the end-expiration moment according to the expiratory flow rate during the exhalation process and calculates the inspiratory tidal volume corresponding to the end-inspiration moment according to the inspiratory flow rate during the inspiration process, so as to obtain the respiratory tidal volume of the user, which can achieve accurate detection of the tidal volume and improve the accuracy of subsequent calculations.

[0119] Based on the above embodiments, Figure 4 is a schematic flowchart of another pulmonary function parameter detection method provided by the embodiments of the present application. As Figure 4 shown, the detection of the pulmonary function parameter may specifically include:

[0120] S401. Collect the respiratory parameters of the user; the respiratory parameters include expiratory pressure data, expiratory time data, and respiratory tidal volume.

[0121] S402. Determine the gas leakage volume of the user according to the difference between the inspiratory tidal volume and the expiratory tidal volume in the respiratory tidal volume.

[0122] In the embodiments of the present application, the gas leakage volume may refer to the gas leakage volume during the exhalation stage of the user, and may specifically be represented by V leak . The anesthesia machine can calculate the difference between the inspiratory tidal volume and the expiratory tidal volume to obtain the gas leakage volume. Exemplarily, the gas leakage volume can be specifically determined by the following formula (1):

[0123] V leak =V insp -V exp (1)

[0124] S403. Determine the cumulative expiratory pressure data corresponding to the user according to the expiratory pressure data and the expiratory time data.

[0125] S404. Determine the leakage coefficient based on the gas leakage volume and the cumulative expiratory pressure data.

[0126] In the embodiments of the present application, the cumulative expiratory pressure data may refer to the cumulative value of the pressure corresponding to the user during the exhalation stage with respect to time, for example, it may refer to the integral value of the expiratory pressure with respect to time, etc.

[0127] Specifically, there is usually a certain gas leakage in the anesthesia machine, and the number of leakage points can be at least one. At this time, at least one leakage point of the anesthesia machine can be equivalent to a leakage port. The leakage coefficient K of this leakage port leakThe model can be expressed by the following formula (2):

[0128] K leak = P(t) / f leak (t) (2)

[0129] In formula (2), P(t) is the real-time pressure during the exhalation phase in the ventilation circuit of the anesthesia machine, that is, the exhalation pressure values at different exhalation moments included in the exhalation pressure data, and f leak (t) is the real-time leakage flow rate of the leakage port during the exhalation phase. On this basis, the total gas leakage volume V leak and the relationship between the leakage flow rate of the leakage port can be expressed by the following formula (3):

[0130]

[0131] According to the above formula (3) and formula (1), the leakage coefficient K leak can be expressed by the following formula (4):

[0132]

[0133] In this way, in the embodiment of the present application, after the anesthesia machine collects the user's exhalation pressure data, exhalation time data, and tidal volume of respiration, it can first determine the user's gas leakage volume according to the difference between the inspiratory tidal volume and the exhalation tidal volume, and then calculate the cumulative exhalation pressure data of the user by means of integral calculation according to the exhalation pressure data and exhalation time data; then determine the ratio of the gas leakage volume to the cumulative exhalation pressure data as the leakage coefficient of the user's corresponding breathing circuit system, realizing the quantitative processing of gas leakage during the user's exhalation process, and improving the accuracy of subsequent calculation of lung function parameters.

[0134] S405. Determine the target correlation relationship among the expiratory phase comprehensive time constant, expiratory phase additional time constant, and expiratory phase physiological time constant according to the leakage coefficient.

[0135] In the embodiment of the present application, the expiratory phase time parameters include the expiratory phase comprehensive time constant, the expiratory phase additional time constant, and the expiratory phase physiological time constant. The target correlation relationship may refer to the correlation relationship among different time constants in the expiratory phase time parameters. The anesthesia machine can specifically calculate the target correlation relationship by combining the leakage coefficient with the target pressure model. The target pressure model can be created based on the ventilation circuit of the anesthesia machine and the pressure structure of the user's lungs.

[0136] In a possible implementation manner, step S405 can be specifically implemented in the following way:

[0137] According to the target pressure model corresponding to the anesthesia machine, determine the target correlation relationship through the pressure relationship in the target pressure model; wherein, the target pressure model includes a constant pressure source, a circuit pressure, a simulated capacitor, a simulated resistor, and a leakage air resistance; the simulated capacitor and the simulated resistor correspond to lung function parameters.

[0138] In the embodiment of the present application, the target pressure model may refer to a simplified pressure model created for the ventilation circuit of the anesthesia machine and the lung pressure of the user during the exhalation process of the user. Specifically, the target pressure model may include a constant pressure source, a circuit pressure, a simulated capacitor, a simulated resistor, and a leakage air resistance, etc. Among them, the constant pressure source pressure can be expressed as P s . The circuit pressure can be expressed as P aw . The simulated capacitor may refer to a capacitor created based on the compliance of the user's exhalation phase; the simulated resistor may refer to a resistor created based on the air resistance of the user's exhalation phase. The leakage air resistance may refer to a resistor created based on the leakage coefficient of the user.

[0139] Exemplarily, Figure 5 is a schematic diagram of a target pressure model provided by an embodiment of the present application. As Figure 5 shown, the target pressure model may specifically include a constant pressure source, a circuit pressure, a simulated capacitor, a simulated resistor, and a leakage air resistance. According to this target pressure model, the relationship between the constant pressure source pressure P s and the circuit pressure P aw can be expressed by the following formula (5):

[0140]

[0141] wherein, R phy is the exhalation phase air resistance, C phy is the exhalation phase compliance, R leak =K leak is the leakage simplified air resistance, s represents a dimension in the Laplace transform, and usually takes a complex number value. Simplifying the above formula (5), the target correlation relationship can be obtained, which can be specifically expressed as the following formulas (6) to (9):

[0142] τ L =C phy R leak (6)

[0143] τ phy =C phy R phy (7)

[0144]

[0145] wherein, τ L is the exhalation phase additional time constant, τ phy is the exhalation phase physiological time constant, τsyn It is the expiratory phase comprehensive time constant. In this way, based on the pressure relationship of the target pressure model, the anesthesia machine can determine the correlation relationship between different time constants, which can improve the convenience and accuracy of subsequent calculations of each time constant.

[0146] S406. Determine the user's expiratory phase time parameter according to the expiratory pressure data, expiratory time data, and the target correlation relationship.

[0147] In the embodiment of the present application, after the anesthesia machine determines the target correlation relationship, it can determine the user's expiratory phase time parameter according to this correlation relationship, the user's expiratory pressure data, and expiratory time data, realizing quantitative processing for gas leakage, being able to eliminate the influence of gas leakage on the detection of lung function parameters, and improving the accuracy of subsequent lung function detection.

[0148] In a possible implementation manner, step S406 can be specifically implemented through the following steps S4061 to S4063:

[0149] S4061. Determine the exponential decay function corresponding to the expiratory pressure decline process, and based on the exponential decay function, determine the correlation relationship between the expiratory phase comprehensive time constant, expiratory pressure value, and expiratory moment.

[0150] S4062. Determine the expiratory phase comprehensive time constant according to the expiratory pressure data, expiratory time data, and the correlation relationship.

[0151] In the embodiment of the present application, the exponential decay function may refer to the decay characteristic function corresponding to the expiratory pressure decline process in the ventilation circuit between the user and the anesthesia machine during the expiratory process. Specifically, in the embodiment of the present application, the anesthesia machine and the patient before the closed-loop control of the expiratory valve during the expiratory process are simplified to a first-order system. During this period, the pressure decline process conforms to the exponential decay characteristic, and this exponential decay function can be expressed by the following formula (10):

[0152]

[0153] where P(t) is the expiratory pressure during the decay process, and P0 is the initial expiratory pressure.

[0154] Take the logarithm of both sides of formula (10) and simplify as follows:

[0155]

[0156] Let x(t) = lnP(t) - lnP0, and the above formula is transformed into the form of a straight-line equation:

[0157] t = τ syn ·x(t) (12)

[0158] According to the relationship between the expiratory phase comprehensive time constant and pressure in formula (12), based on the expiratory pressure value sequence corresponding to the expiratory pressure data and the expiratory moment sequence corresponding to the expiratory time data, through estimation algorithms such as the linear least squares method, the expiratory phase comprehensive time constant is estimated, and the correlation relationship between the expiratory phase comprehensive time constant, the expiratory pressure value, and the expiratory moment can be obtained. This correlation relationship can be expressed by the following formula (13):

[0159]

[0160] Among them, is the mean value of x(t i ), and i represents different expiratory moments. In this way, based on the correlation relationship between the expiratory phase comprehensive time constant, the expiratory pressure value, and the expiratory moment, the anesthesia machine substitutes the actually detected expiratory pressure data and expiratory time data, and the expiratory phase comprehensive time constant can be calculated.

[0161] S4063. Determine the expiratory phase additional time constant and the expiratory phase physiological time constant according to the expiratory pressure data, the expiratory time data, the expiratory phase comprehensive time constant, and the target correlation relationship.

[0162] In the embodiments of the present application, after determining the expiratory phase comprehensive time constant, the anesthesia machine can further determine the expiratory phase additional time constant and the expiratory phase physiological time constant of the user based on the expiratory phase comprehensive time constant, the user's expiratory pressure data and expiratory time data, and in combination with the target correlation relationship between different time constants. Specifically, the expiratory phase comprehensive time constant can be substituted into formula (9) and converted into a time domain equation, and the following formula (14) can be obtained:[[]]

[0163]

[0164] Some parameters in formula (14) can be expressed in the following form:[[]]

[0165]

[0166] In this way, formula (16) can be simplified to:[[]]

[0167] y1(t) = θ1 · x1(t) (18)

[0168] According to formula (18), calculate θ1 through preset estimation algorithms such as the linear least squares method:[[]]

[0169]

[0170] Among them, is the mean value of x1(t i ),

[0171] After calculating the expiratory phase comprehensive time constant τ syn and θ1, combining Formula (8) and Formula (15) to obtain the expiratory phase physiological time constant τ phy and the expiratory phase additional time constant τ L :

[0172]

[0173] In this way, in the embodiment of the present application, the anesthesia machine calculates the intermediate parameter expiratory phase comprehensive time constant τ syn first according to the user's expiratory pressure data, expiratory time data, and the correlation between the expiratory phase comprehensive time constant and the expiratory pressure value and expiratory moment, then calculates the intermediate parameter θ1 according to the expiratory pressure data and expiratory time data, and further calculates the expiratory phase physiological time constant τ phy and the expiratory phase additional time constant τ L based on the target correlation between the three time constants, realizing the accurate calculation of the expiratory phase time parameters and improving the accuracy of subsequent user lung function parameter detection.

[0174] S407. Determine the expiratory phase compliance according to the leakage coefficient and the expiratory phase additional time constant; determine the expiratory phase airway resistance based on the expiratory phase physiological time constant and the expiratory phase compliance.

[0175] In the embodiment of the present application, the lung function parameters include at least one of the expiratory phase compliance and the expiratory phase airway resistance. Specifically, after the anesthesia machine determines the leakage coefficient of the breathing circuit system corresponding to the user and the expiratory phase time parameters, it can further determine the user's expiratory phase compliance according to the leakage coefficient and the expiratory phase additional time constant; at the same time, it can determine the user's expiratory phase airway resistance based on the expiratory phase physiological time constant and the expiratory phase compliance.

[0176] Exemplarily, combining the above Formulas (6), (7), (21), and (22), the patient's expiratory phase compliance of the user can be expressed by the following Formula (22), and the expiratory phase airway resistance of the user can be expressed by the following Formula (23):

[0177]

[0178] In this way, after the anesthesia machine in the embodiment of the present application determines the leakage coefficient K leak of the breathing circuit system corresponding to the user and the expiratory phase time parameters, substituting them into the above Formulas (22) and (23), the lung function parameters during the user's exhalation process can be obtained.

[0179] S408. During the current breathing process, display the user's pulmonary function parameters during the previous breathing process on the display screen.

[0180] In the embodiment of the present application, after the anesthesia machine determines the pulmonary function parameters during the user's exhalation process, it can display the pulmonary function parameters on the display screen. As the user continues to breathe, the display screen can display the user's pulmonary function parameters during the previous breathing process during the current breathing process. In this way, dynamic detection and display of the user's pulmonary function parameters can be realized, and the intuitiveness of the display of pulmonary function parameters can be improved.

[0181] Based on the above embodiment, Figure 6 is a logical schematic diagram of pulmonary function parameter detection provided by the embodiment of the present application. As Figure 6 shown, the anesthesia machine first collects the user's breathing parameters, which can specifically include the user's expiratory pressure data, expiratory time data, and tidal volume of breathing. Then the anesthesia machine can calculate the leakage coefficient of the corresponding breathing circuit system of the user. Specifically, it can calculate the gas leakage amount according to the inspiratory tidal volume and the expiratory tidal volume, and calculate the linear relationship coefficient between the leakage flow rate at the leakage port and the expiratory pressure based on the gas leakage amount and the change in expiratory pressure, which is the leakage coefficient.

[0182] After that, the anesthesia machine can determine the target correlation relationship among the expiratory phase comprehensive time constant, the expiratory phase additional time constant, and the expiratory phase physiological time constant according to the target pressure model. Then it can calculate the correlation relationship between the expiratory phase comprehensive time constant and the expiratory pressure value and the expiratory moment according to the exponential decay function, and calculate the expiratory phase comprehensive time constant based on a preset estimation algorithm (such as the least squares method, etc.). Furthermore, based on the expiratory phase comprehensive time constant and the target correlation relationship, the expiratory phase additional time constant and the expiratory phase physiological time constant are determined to realize the calculation of the expiratory phase time parameters.

[0183] After calculating the leakage coefficient and the expiratory phase time parameters, the anesthesia machine can calculate the user's expiratory phase compliance, expiratory phase airway resistance and other pulmonary function parameters according to the leakage coefficient, the expiratory phase additional time constant, and the expiratory phase physiological time constant, so as to realize the accurate detection of pulmonary function parameters.

[0184] In the pulmonary function parameter detection method in the embodiment of the present application, by introducing the leakage coefficient, the expiratory phase comprehensive time constant, and the expiratory phase additional time constant, the expiratory phase comprehensive time constant, the expiratory phase additional time constant, and the expiratory phase physiological time constant are calculated by using the exponential decay function and the preset estimation algorithm during the expiratory phase. In this way, the anesthesia machine quantifies the gas leakage amount during the calculation process, thereby avoiding the influence of the gas leakage amount on the detection of pulmonary function parameters, improving the accuracy of the detection of pulmonary function parameters, and providing more reliable data support for anesthesia treatment.

[0185] Figure 7 This is a schematic structural diagram of a pulmonary function parameter detection device provided by an embodiment of the present application. Please refer to Figure 7 , the pulmonary function parameter detection device 70 may include:

[0186] An acquisition module 71, configured to acquire the breathing parameters of a user; the breathing parameters include expiratory pressure data, expiratory time data, and tidal volume of breathing;

[0187] A first determination module 72, configured to determine the leakage coefficient of the breathing circuit system corresponding to the user based on the breathing parameters;

[0188] A second determination module 73, configured to determine the expiratory phase time parameter of the user according to the leakage coefficient, expiratory pressure data, and expiratory time data;

[0189] A third determination module 74, configured to determine the pulmonary function parameter of the user according to the leakage coefficient and the expiratory phase time parameter.

[0190] In a possible implementation manner, the acquisition module 71 is specifically configured to:

[0191] Determine the expiratory start pressure and expiratory start moment according to the change of the breathing flow rate, and open the expiratory valve of the anesthesia machine;

[0192] During the process of the expiratory pressure dropping, record the expiratory moment and the corresponding expiratory pressure value within each preset sampling period according to the preset sampling period;

[0193] When the expiratory pressure drops to the preset pressure value, perform closed-loop control on the expiratory valve, and stop recording the expiratory moment and the expiratory pressure value, so as to obtain the expiratory pressure data and the expiratory time data.

[0194] In a possible implementation manner, the acquisition module 71 is specifically configured to:

[0195] Determine the end-inspiration moment and end-expiration moment corresponding to the user according to the change of the breathing flow rate;

[0196] Calculate the inspiratory tidal volume at the end-inspiration moment according to the inspiratory flow rate during the inspiration process, and calculate the expiratory tidal volume at the end-expiration moment according to the expiratory flow rate during the expiration process, so as to obtain the tidal volume of breathing of the user.

[0197] In a possible implementation manner, the first determination module 72 is specifically configured to:

[0198] Determine the gas leakage amount of the user according to the difference between the inspiratory tidal volume and the expiratory tidal volume in the tidal volume of breathing;

[0199] Determine the cumulative expiratory pressure data corresponding to the user according to the expiratory pressure data and the expiratory time data;

[0200] Determine the leakage coefficient of the user based on the gas leakage volume and the cumulative expiratory pressure data.

[0201] In a possible implementation manner, the expiratory phase time parameter includes an expiratory phase comprehensive time constant, an expiratory phase additional time constant, and an expiratory phase physiological time constant; the second determination module 73 is specifically configured to:

[0202] Determine the target correlation relationship among the expiratory phase comprehensive time constant, the expiratory phase additional time constant, and the expiratory phase physiological time constant according to the leakage coefficient;

[0203] Determine the expiratory phase time parameter of the user according to the expiratory pressure data, the expiratory time data, and the target correlation relationship.

[0204] In a possible implementation manner, the second determination module 73 is specifically configured to:

[0205] Determine the target correlation relationship according to the target pressure model corresponding to the anesthesia machine through the pressure relationship in the target pressure model;

[0206] Wherein, the target pressure model includes a constant pressure source, a circuit pressure, a simulation capacitor, a simulation resistor, and a leakage air resistance; the simulation capacitor and the simulation resistor correspond to the lung function parameters.

[0207] In a possible implementation manner, the second determination module 73 is specifically configured to:

[0208] Determine the exponential decay function corresponding to the expiratory pressure decline process, and determine the correlation relationship among the expiratory phase comprehensive time constant, the expiratory pressure value, and the expiratory moment according to the exponential decay function;

[0209] Determine the expiratory phase comprehensive time constant according to the expiratory pressure data, the expiratory time data, and the correlation relationship;

[0210] Determine the expiratory phase additional time constant and the expiratory phase physiological time constant according to the expiratory pressure data, the expiratory time data, the expiratory phase comprehensive time constant, and the target correlation relationship.

[0211] In a possible implementation manner, the lung function parameter includes at least one of the expiratory phase compliance and the expiratory phase air resistance; the third determination module 74 is specifically configured to:

[0212] Determine the expiratory phase compliance according to the leakage coefficient and the expiratory phase additional time constant;

[0213] Determine the expiratory phase air resistance based on the expiratory phase physiological time constant and the expiratory phase compliance.

[0214] In a possible implementation, the device 70 is further configured to:

[0215] During the current breathing process, display the user's lung function parameters during the previous breathing process on the display screen.

[0216] The lung function parameter detection device 70 provided by the embodiments of the present application can execute the technical solutions shown in the above method embodiments, and the implementation principles and beneficial effects are similar, which will not be elaborated here.

[0217] Figure 8 It is a schematic structural diagram of a lung function parameter detection device provided by the embodiments of the present application. Please refer to Figure 8 , the lung function parameter detection device 80 may include: a memory 81 and a processor 82. Exemplarily, the memory 81 and the processor 82 are interconnected with each other through a bus 83.

[0218] The memory 81 is used to store program instructions;

[0219] The processor 82 is used to execute the program instructions stored in the memory to implement the lung function parameter detection method shown in the above embodiments.

[0220] Figure 8 The shown lung function parameter detection device 80 can execute the technical solutions shown in the above method embodiments, and the implementation principles and beneficial effects are similar, which will not be elaborated here.

[0221] The embodiments of the present application provide a computer-readable storage medium, in which computer-executable instructions are stored, and when the computer-executable instructions are executed by a processor, they are used to implement the above lung function parameter detection method.

[0222] The embodiments of the present application can also provide a computer program product, including a computer program, and when the computer program is executed by a processor, the above lung function parameter detection method can be implemented.

[0223] The embodiments of the present application also provide an anesthesia machine, which can implement the above lung function parameter detection method.

[0224] It should be noted that the processor mentioned in the embodiments of the present application may be a central processing unit (CPU), or may also be other general-purpose processors, digital signal processors (DSPs), application specific integrated circuits (ASICs), field programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc.

[0225] It should be understood that the memory mentioned in the embodiments of the present application may be a volatile memory or a non-volatile memory, or may include both volatile and non-volatile memories. Among them, the non-volatile memory may be a read-only memory (ROM), a programmable ROM (PROM), an erasable programmable ROM (EPROM), an electrically erasable programmable ROM (EEPROM), or a flash memory. The volatile memory may be a random access memory (RAM), which is used as an external cache. By way of example but not limitation, many forms of RAM are available, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate synchronous DRAM (DDR SDRAM), enhanced SDRAM (ESDRAM), synch link DRAM (SLDRAM), and direct ram bus RAM (DR RAM). It should be noted that when the processor is a general-purpose processor, DSP, ASIC, FPGA, or other programmable logic device, discrete gate or transistor logic device, discrete hardware component, the memory (storage module) is integrated in the processor. It should be noted that the memory described herein is intended to include, but is not limited to, these and any other suitable types of memory.

[0226] It should be understood that in various embodiments of the present application, the sequence numbers of the above processes do not indicate the order of execution, and the order of execution of each process should be determined by its function and internal logic, and should not constitute any limitation to the implementation process of the embodiments of the present application.

[0227] Embodiments of the present application are described with reference to the flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present application. It should be understood that each process and / or block in the flowchart and / or block diagram, and the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to the processing unit of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to generate a machine, so that the instructions executed by the processing unit of the computer or other programmable data processing devices generate a device for implementing the functions specified in one process Figure 1 one process or multiple processes and / or blocks Figure 1 or multiple blocks.

[0228] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer-readable memory generate a manufactured article including an instruction device, and the instruction device implements the functions specified in one process Figure 1 one process or multiple processes and / or blocks Figure 1 or multiple blocks.

[0229] These computer program instructions can also be loaded onto a computer or other programmable data processing device, so that a series of operation steps are executed on the computer or other programmable device to generate a computer-implemented process, and thus the instructions executed on the computer or other programmable device provide steps for implementing the functions specified in one process Figure 1 one process or multiple processes and / or blocks Figure 1 or multiple blocks.

[0230] Regarding each device and product described in the above embodiments, each module / unit included therein can be a software module / unit, a hardware module / unit, or can also be partially a software module / unit and partially a hardware module / unit. Each device and product can be applied to or integrated into a chip, a chip module, or a terminal device. Exemplarily, for each device and product applied to or integrated into a chip, each module / chip included therein can be implemented in the form of hardware such as circuits, or at least some modules / units can be implemented in the form of software programs, and the software programs run on a processor integrated inside the chip, and the remaining part of the modules / units can be implemented in the form of hardware such as circuits.

[0231] In this application, the term "including" and its variants may refer to non-limiting inclusion; the term "or" and its variants may refer to "and / or". In this application, terms such as "first", "second", etc. are used to distinguish similar objects and do not necessarily describe a specific order or sequence. In this application, "a plurality of" means two or more. "And / or" describes the relationship between related objects and indicates that three relationships may exist. For example, A and / or B may represent three situations: A exists alone, A and B exist simultaneously, and B exists alone. The character " / " generally indicates that the related objects before and after are in an "or" relationship.

[0232] The above are only partial embodiments of this application. It should be noted that for those of ordinary skill in the art, without departing from the principle of this application, several improvements and refinements can be made, and these improvements and refinements should also be regarded as the protection scope of this application.

Claims

1. A method for detecting pulmonary function parameters, characterized in that, Comprising: Collecting the breathing parameters of a user; The breathing parameters include expiratory pressure data, expiratory time data, and tidal volume of breathing; Based on the breathing parameters, determining the leakage coefficient of the breathing circuit system corresponding to the user; According to the leakage coefficient, the expiratory pressure data, and the expiratory time data, determining the expiratory phase time parameters of the user, where the expiratory phase time parameters include an expiratory phase comprehensive time constant, an expiratory phase additional time constant, and an expiratory phase physiological time constant; According to the leakage coefficient and the expiratory phase time parameters, determining the lung function parameters of the user; Wherein, the lung function parameters include expiratory phase compliance and expiratory phase airway resistance; the determining the lung function parameters of the user according to the leakage coefficient and the expiratory phase time parameters includes: Determining the expiratory phase compliance according to the leakage coefficient and the expiratory phase additional time constant; Based on the expiratory phase physiological time constant and the expiratory phase compliance, determining the expiratory phase airway resistance.

2. The method according to claim 1, wherein The collecting the breathing parameters of the user includes: According to the change of breathing flow rate, determining the starting expiratory pressure and the starting expiratory moment, and opening the expiratory valve of the anesthesia machine; During the process of the expiratory pressure dropping, recording the expiratory moment and the expiratory pressure value corresponding to the expiratory moment in each preset sampling period according to the preset sampling period; When the expiratory pressure drops to a preset pressure value, performing closed-loop control on the expiratory valve, and stopping recording the expiratory moment and the expiratory pressure value, to obtain the expiratory pressure data and the expiratory time data.

3. The method according to claim 1, characterized in that, The collecting the breathing parameters of the user includes: According to the change of breathing flow rate, determining the end-inspiratory moment and the end-expiratory moment corresponding to the user; Calculating the inspiratory tidal volume at the end-inspiratory moment according to the inspiratory flow rate during the inspiratory process, and calculating the expiratory tidal volume at the end-expiratory moment according to the expiratory flow rate during the expiratory process, to obtain the tidal volume of breathing of the user.

4. The method according to claim 1, wherein The determining the leakage coefficient of the breathing circuit system corresponding to the user based on the breathing parameters includes: According to the difference between the inspiratory tidal volume and the expiratory tidal volume in the tidal volume of breathing, determining the gas leakage amount of the user; According to the expiratory pressure data and the expiratory time data, determining the cumulative expiratory pressure data corresponding to the user; Based on the gas leakage amount and the cumulative expiratory pressure data, determining the leakage coefficient.

5. The method according to claim 1, characterized in that, The determining the expiratory phase time parameters of the user according to the leakage coefficient, the expiratory pressure data, and the expiratory time data includes: According to the leakage coefficient, determining the target correlation relationship between the expiratory phase comprehensive time constant, the expiratory phase additional time constant, and the expiratory phase physiological time constant; According to the expiratory pressure data, the expiratory time data, and the target correlation relationship, determining the expiratory phase time parameters of the user.

6. The method according to claim 5, wherein The determining the target correlation relationship between the expiratory phase comprehensive time constant, the expiratory phase additional time constant, and the expiratory phase physiological time constant includes: Determine the target correlation relationship according to the target pressure model corresponding to the anesthesia machine through the pressure relationship in the target pressure model; Among them, the target pressure model includes a constant pressure source, a circuit pressure, a simulated capacitor, a simulated resistor, and a leakage air resistance; the simulated capacitor and the simulated resistor correspond to the lung function parameters.

7. The method according to claim 5, characterized in that The determining the expiratory phase time parameter of the user according to the expiratory pressure data, the expiratory time data, and the target correlation relationship includes: Determine the exponential decay function corresponding to the expiratory pressure drop process, and according to the exponential decay function, determine the correlation relationship between the comprehensive expiratory time constant, the expiratory pressure value, and the expiratory moment; Determine the comprehensive expiratory time constant according to the expiratory pressure data, the expiratory time data, and the correlation relationship; Determine the additional expiratory time constant and the physiological expiratory time constant according to the expiratory pressure data, the expiratory time data, the comprehensive expiratory time constant, and the target correlation relationship.

8. The method according to claim 1, characterized in that, The method further includes: During the current breathing process, display the lung function parameters of the user during the previous breathing process on the display screen.

9. An anesthetic machine, characterized in that, The anesthesia machine can implement the lung function parameter detection method according to any one of claims 1 to 8.

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