Ventilator pressure sensor detection method and device

Abstract

The present invention provides a ventilator pressure sensor detection method and device, wherein the ventilator includes a pressure sensor for real-time acquisition of the pressure signal in the ventilator airway, firstly generating a detection signal corresponding to the pressure sensor based on preset signal parameters, then generating a pressure feedback signal corresponding to the pressure sensor based on a preset closed-loop transfer function, a preset target pressure value and the detection signal, then sampling the pressure feedback signal at a second sampling rate through a preset sliding window to obtain a pressure feedback sample corresponding to the pressure sensor in real time, and then determining a discrete index of the pressure feedback sample obtained by each sampling, and if an abnormal event occurs in which the discrete index is less than a preset discrete index threshold, the pressure sensor is determined to have failed. The present invention can alleviate the problem of low efficiency and accuracy of existing ventilator pressure sensor failure detection methods.

Description

Technical Field

[0001] The present invention relates to the technical field of medical equipment, and in particular to a method and device for detecting a ventilator pressure sensor. Background Art

[0002] The pressure sensor is one of the important sensors in a home ventilator. The closed-loop pressure control of the ventilator is mainly achieved by the controller, the fan, and the pressure sensor. The stability and safety of the pressure control are important performances in a home ventilator. Overpressure protection during the use of the ventilator is a link that must be considered in the design of the ventilator. Overpressure protection needs to consider overpressure prevention under normal working conditions of the ventilator and sensor failure detection. The overpressure prevention logic mainly includes: the pressure sensor is connected to the ventilator airway to collect airway pressure in real time, and the controller converts the pressure analog signal into a digital signal for logical judgment. When the controller detects that the pressure exceeds the maximum design pressure value and lasts for a period of time (usually a few seconds), the controller controls the fan to shut down and generates an alarm signal. When the sensor fails, overpressure protection cannot be generated. The existing technology mainly determines whether the pressure sensor has failed by detecting whether the maximum and minimum values ​​of the pressure signal collected by the pressure sensor exceed the threshold range by the controller. For example, when the controller detects that the maximum and / or minimum values ​​of the pressure signal collected by the pressure sensor exceed the threshold range, the controller can determine that the pressure sensor has failed.

[0003] However, the existing technology of only judging whether the maximum and minimum values ​​of the pressure signal collected by the pressure sensor exceed the threshold range has certain limitations in the actual use of ventilators. For example, when the user uses the CPAP (Continuous Positive Airway Pressure) mode to set the ventilator to work at a constant pressure, once the pressure sensor fails, the ventilator will lose the ability to maintain a constant respiratory pressure on the patient end, and the expected therapeutic effect will not be achieved. However, sometimes the pressure sensor has actually failed but it still takes some time to detect that the maximum and / or minimum values ​​of the pressure signal collected by the pressure sensor exceed the threshold range. Therefore, the existing ventilator pressure sensor failure detection method actually has a certain hysteresis, and the detection efficiency and accuracy are low. Summary of the Invention

[0004] In view of this, an object of the present invention is to provide a method and device for detecting a ventilator pressure sensor, so as to alleviate the above-mentioned problems existing in the existing ventilator pressure sensor failure detection method.

[0005] In a first aspect, an embodiment of the present invention provides a method for detecting a ventilator pressure sensor, wherein the ventilator includes a pressure sensor for real-time acquisition of a pressure signal in an airway of the ventilator, the method comprising: generating a detection signal corresponding to the pressure sensor based on preset signal parameters; wherein the detection signal is a discrete signal, and the preset signal parameters include amplitude, frequency, and a first sampling rate; generating a pressure feedback signal corresponding to the pressure sensor based on a preset closed-loop transfer function, a preset target pressure value, and the detection signal; sampling the pressure feedback signal at a second sampling rate using a preset sliding window to obtain pressure feedback samples corresponding to the pressure sensor in real time; wherein the size of the preset sliding window is determined based on the first sampling rate and the frequency, the second sampling rate is determined based on the frequency, and the number of pressure feedback samples obtained in each sampling is consistent with the size of the preset sliding window; determining a discrete index of the pressure feedback sample obtained in each sampling, and determining that the pressure sensor has failed if an abnormal event occurs in which the discrete index is less than a preset discrete index threshold; wherein the discrete index represents the degree of discreteness of the pressure feedback samples obtained in the corresponding sampling.

[0006] In a second aspect, an embodiment of the present invention further provides a ventilator pressure sensor detection device, the ventilator including a pressure sensor for real-time acquisition of an airway pressure signal of the ventilator, the device comprising: a first generation module for generating a detection signal corresponding to the pressure sensor based on preset signal parameters; wherein the detection signal is a discrete signal, and the preset signal parameters include amplitude, frequency, and a first sampling rate; a second generation module for generating a pressure feedback signal corresponding to the pressure sensor based on a preset closed-loop transfer function, a preset target pressure value, and the detection signal; a sampling module for sampling the pressure feedback signal at a second sampling rate through a preset sliding window to obtain pressure feedback samples corresponding to the pressure sensor in real time; wherein the size of the preset sliding window is determined based on the first sampling rate and the frequency, and the second sampling rate is determined based on the frequency, and the number of pressure feedback samples obtained in each sampling is consistent with the size of the preset sliding window; and a determination module for determining a discrete index of the pressure feedback sample obtained in each sampling, and determining that the pressure sensor has failed if an abnormal event occurs in which the discrete index is less than a preset discrete index threshold; wherein the discrete index represents the degree of discreteness of the pressure feedback samples obtained in the corresponding sampling.

[0007] An embodiment of the present invention provides a ventilator pressure sensor detection method and device, in which the ventilator includes a pressure sensor for real-time acquisition of the pressure signal in the ventilator airway, first generating a detection signal corresponding to the pressure sensor based on preset signal parameters, then generating a pressure feedback signal corresponding to the pressure sensor based on a preset closed-loop transfer function, a preset target pressure value and the detection signal, and then sampling the pressure feedback signal at a second sampling rate through a preset sliding window to obtain the pressure feedback sample corresponding to the pressure sensor in real time, and then determining the discrete index of the pressure feedback sample obtained by each sampling, and if an abnormal event occurs in which the discrete index is less than the preset discrete index threshold, the pressure sensor is determined to have failed. By adopting the above technology, the failure detection of the ventilator pressure sensor can be realized by sampling the generated pressure feedback signal through a preset sliding window using the generated detection signal, and the detection efficiency and accuracy are both high, thereby alleviating the problem of low efficiency and accuracy of the existing ventilator pressure sensor failure detection method.

[0008] Other features and advantages of the present invention will be described in the following description, and in part will become apparent from the description, or understood by practicing the present invention. The purposes and other advantages of the present invention are realized and obtained by the structures particularly pointed out in the description, claims and drawings.

[0009] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, preferred embodiments are given below and described in detail with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0010] In order to more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the specific embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0011] Figure 1 Schematic diagram of a flow chart of a method for detecting a ventilator pressure sensor in an embodiment of the present invention;

[0012] Figure 2 This is a block diagram of the closed-loop pressure control of a ventilator in an embodiment of the present invention;

[0013] Figure 3 This is a structural diagram of a ventilator pressure sensor detection device according to an embodiment of the present invention;

[0014] Figure 4 Schematic diagram of the structure of another ventilator pressure sensor detection device in an embodiment of the present invention. DETAILED DESCRIPTION

[0015] To make the objectives, technical solutions, and advantages of the embodiments of the present invention more clear, the technical solutions of the present invention will be clearly and completely described below in conjunction with the embodiments. Obviously, the embodiments described are only part of the embodiments of the present invention, not all of them. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0016] To facilitate understanding of this embodiment, a ventilator pressure sensor detection method disclosed in an embodiment of the present invention is first described in detail. The ventilator may include a pressure sensor for real-time acquisition of the pressure signal in the airway of the ventilator, see Figure 1 As shown, the method may include the following steps:

[0017] Step S102: generating a detection signal corresponding to the pressure sensor based on preset signal parameters.

[0018] The detection signal is a discrete signal, and the preset signal parameters include amplitude, frequency and a first sampling rate.

[0019] When generating a detection signal, a continuous signal with amplitude and frequency may be generated as an initial detection signal, and then the initial detection signal may be sampled according to a first sampling rate to obtain a discrete signal as the desired detection signal.

[0020] Step S104 : generating a pressure feedback signal corresponding to the pressure sensor based on a preset closed-loop transfer function, a preset target pressure value, and the detection signal.

[0021] Among them, the preset closed-loop transfer function is for a pressure closed-loop control system including a ventilator controller, a pressure sensor and a fan. The preset closed-loop transfer function can be considered as a control system model, and the specific expression form of the preset closed-loop transfer function is not limited here.

[0022] Step S106 : sampling the pressure feedback signal at a second sampling rate through a preset sliding window to obtain pressure feedback samples corresponding to the pressure sensor in real time.

[0023] The size of the preset sliding window is determined based on the first sampling rate and the frequency, the second sampling rate is determined based on the frequency, and the number of pressure feedback samples obtained in each sampling is consistent with the size of the preset sliding window.

[0024] A sliding window can be generated in advance according to the first sampling rate and frequency. When the pressure feedback signal is sampled at the second sampling rate through the sliding window, each sampling point within the sliding window obtained by sampling can be used as a pressure feedback sample each time the sliding window is sampled, that is, each sampling will obtain pressure feedback samples within the sliding window and the number of which is consistent with the sliding window.

[0025] Step S108 , determining a discrete index of the pressure feedback sample obtained in each sampling. If an abnormal event occurs in which the discrete index is less than a preset discrete index threshold, it is determined that the pressure sensor has failed.

[0026] The discrete index represents the degree of discreteness of the pressure feedback samples obtained by the corresponding sampling. For example, the discrete index can be the range, standard deviation, variance, quartile, coefficient of variation, etc., which are not limited to this.

[0027] Since the pressure feedback signal corresponding to a ventilator pressure sensor in a normal state generally exhibits certain fluctuations (i.e., a relatively high degree of discreteness), and the pressure feedback signal corresponding to a ventilator pressure sensor in a failed state is generally relatively stable (i.e., a relatively low degree of discreteness, even reaching or approaching zero), the discreteness of the pressure feedback signal can be used to reflect whether the pressure sensor has failed. Continuing with the previous example, for each pressure feedback sample obtained through the sliding window, the discreteness of the pressure feedback sample obtained for that sampling can be characterized by calculating a discrete index. This allows the pressure sensor to be determined to have failed when the discrete index of the pressure feedback sample obtained from one or more samplings is less than a preset discrete index threshold.

[0028] An embodiment of the present invention provides a method for detecting a ventilator pressure sensor, in which the ventilator includes a pressure sensor for real-time acquisition of a pressure signal in the airway of the ventilator. A detection signal corresponding to the pressure sensor is first generated based on preset signal parameters, and then a pressure feedback signal corresponding to the pressure sensor is generated based on a preset closed-loop transfer function, a preset target pressure value, and the detection signal. The pressure feedback signal is then sampled at a second sampling rate through a preset sliding window to obtain a pressure feedback sample corresponding to the pressure sensor in real time, and then a discrete index of the pressure feedback sample obtained by each sampling is determined. If an abnormal event occurs in which the discrete index is less than a preset discrete index threshold, the pressure sensor is determined to have failed. By adopting the above technology, the failure detection of the ventilator pressure sensor can be realized by sampling the generated pressure feedback signal through a preset sliding window using the generated detection signal. The detection efficiency and accuracy are both high, thereby alleviating the problem of low efficiency and accuracy of the existing ventilator pressure sensor failure detection method.

[0029] As a possible implementation, the above step S102 (i.e., generating a detection signal corresponding to the pressure sensor based on the preset signal parameters) may include:

[0030] Based on the preset signal parameters, the following formula is used to generate the initial detection signal:

[0031] y=A*(1+sin(2π*Freq*(N / Fs)))

[0032] Where y is the initial detection signal, A is the amplitude, Freq is the frequency, Fs is the first sampling rate, N is the discrete sampling point number, and the length of each discrete sampling point is Fs / Freq;

[0033] The initial detection signal is converted into the continuous time domain to obtain the detection signal.

[0034] For example, when generating the detection signal D(s), a continuous signal y may be generated based on A and Freq. ′ =A*(1+sin(2π*Freq)), and then calculate y according to Fs and sampling length (i.e. Fs / Freq). ′ Sampling is performed to obtain a discrete signal y, which is then converted to the s domain (i.e., continuous time domain) to obtain D(s).

[0035] As a possible implementation, the above step S104 (i.e., generating a pressure feedback signal corresponding to the pressure sensor based on a preset closed-loop transfer function, a preset target pressure value, and a detection signal) may include:

[0036] Based on the preset closed-loop transfer function, the preset target pressure value and the detection signal, the pressure feedback signal is generated using the following formula:

[0037]

[0038] Wherein, Y(s) is the pressure feedback signal, U(s) is the preset target pressure value, D(s) is the detection signal, and G(s) is the preset closed-loop transfer function.

[0039] See also Figure 2 As shown in the figure, in the closed-loop control process of ventilator pressure, U(s) is the input preset target pressure value, G(s) is the control system model, and D(s) is the input detection signal; by analyzing Figure 2As shown in the ventilator pressure closed-loop control block diagram, when the feedback is normal (i.e., the ventilator pressure sensor is normal), the detection signal D(s) can be fed back to the ventilator controller through the ventilator pressure sensor for signal analysis and processing. When the feedback is missing (i.e., the ventilator pressure sensor fails), the detection signal D(s) cannot be fed back to the ventilator controller through the ventilator pressure sensor for signal analysis and processing. Therefore, whether the ventilator pressure sensor fails can be detected by identifying whether the detection signal D(s) can be fed back to the ventilator controller through the ventilator pressure sensor.

[0040] As a possible implementation, after the above step S104 (i.e., generating a pressure feedback signal corresponding to the pressure sensor based on a preset closed-loop transfer function, a preset target pressure value, and a detection signal), the above ventilator pressure sensor detection method may further include:

[0041] Step 1: Determine the size of a preset sliding window based on a first sampling rate and a frequency to generate a preset sliding window.

[0042] Exemplarily, the operation method of determining the size of the preset sliding window based on the first sampling rate and the frequency in the above step 1 may be: determining that the size of the preset sliding window is not less than the ratio between the first sampling rate and the frequency.

[0043] Step 2: Determine a second sampling rate based on the frequency.

[0044] According to the Nyquist sampling theorem, when sampling an original signal, if the sampling frequency is greater than twice the highest frequency in the original signal, the sampled signal fully retains the information in the original signal. Based on this, the operation method of the above step 2 can be to determine that the second sampling rate is not less than twice the frequency.

[0045] Based on the above steps 1 and 2, when the pressure feedback signal is sampled at the second sampling rate through the sliding window, the pressure feedback samples obtained by the sliding window at each sampling completely retain the information in the pressure feedback signal. Therefore, the discrete degree of the pressure feedback sample obtained at each sampling can fully reflect the discrete degree of the pressure feedback signal, that is, only a small number of discrete sample points need to be collected from the pressure feedback signal to perform discrete index statistics in order to know the discrete degree of the pressure feedback signal, so as to subsequently determine whether the ventilator pressure sensor has failed based on the discrete index.

[0046] As a possible implementation, the discrete index can be determined by statistics of the pressure feedback samples obtained by the corresponding sub-sampling; based on this, determining the discrete index of the pressure feedback sample obtained by each sampling in the above step S108 can include: for the pressure feedback sample obtained by each sampling, calculating the average value and standard deviation of the pressure feedback sample obtained by the sub-sampling, and determining the discrete index corresponding to the sub-sampling based on the average value and standard deviation corresponding to the sub-sampling.

[0047] For example, the discrete indicator may be a coefficient of variation. For each pressure feedback sample obtained by sampling, after calculating the mean value and standard deviation corresponding to the sampling, the coefficient of variation corresponding to the sampling may be calculated based on the mean value and standard deviation corresponding to the sampling using the following formula:

[0048]

[0049] Among them, CV is the coefficient of variation, mean is the mean, and std is the standard deviation.

[0050] For ease of understanding, the operation of the above-mentioned ventilator pressure sensor detection method is described below by taking a specific application as an example.

[0051] The ventilator pressure closed-loop control system mainly consists of the ventilator's MCU, turbine blower and pressure sensor. The ventilator pressure closed-loop control process is as follows: Figure 2 As shown, when the pressure sensor is normal, the system enters closed-loop control and satisfies the following relationship:

[0052]

[0053] Among them, the preset target pressure value U(s) and the detection signal D(s) are both inputs, G(s) is the control system model, and the pressure feedback signal Y(s) is the output, Y(s) = (U(s) - (D(s) + Y(s))) * G(s); through analysis, it can be seen that the change of Y(s) is determined by the input U(s) and D(s). When the feedback is normal, D(s) as input can be fed back to the MCU through the pressure sensor for signal analysis and processing to identify whether the pressure sensor has failed.

[0054] The detection signal D(s) is generated as follows:

[0055] First, use the following formula to generate the initial detection signal:

[0056] y=A*(1+sin(2π*Freq*(N / Fs)))

[0057] Where A is the amplitude (3 in this case), Freq is the frequency (10 Hz in this case), and Fs is the sampling rate (100 Hz in this case). N is the discrete sampling point number (the step size is 1 in this case), and the total length of each discrete sampling point is Fs / Freq (10 in this case).

[0058] The generated initial detection signal y is then converted into a detection signal D(s) in the continuous time domain.

[0059] The ventilator operates at a constant pressure in CPAP mode, meaning the input U(s) remains constant. The MCU continuously samples the pressure feedback signal Y(s) at a sampling frequency of 100Hz. Since the detection signal D(s) has a frequency of 10Hz and a sampling rate of 100Hz, a 100Hz sampling frequency for the pressure sensor feedback signal is more reasonable. This preserves the characteristics of the detection signal D(s), while also minimizing the amount of data collected and analyzed.

[0060] Set the cache sliding window size to 10, and use the MCU to collect data samples of Y(s) at a sampling frequency of 100 Hz to cyclically fill the cache.

[0061] When the number of data samples effectively filled in the cache is equal to 10, calculate the mean and standard deviation std of the 10 data samples and calculate the coefficient of variation The CV value is a normalized measure that reflects the degree of discreteness of the probability distribution of pressure sensor data.

[0062] When the detection signal D(s) is given, if the CV value is greater than the threshold CvCmpVal, the MCU determines that the pressure sensor is normal. If the CV value is not greater than the threshold CvCmpVal, the MCU determines that the pressure sensor is failed and sends an alarm signal so that relevant personnel can deal with the pressure sensor failure in time after receiving the alarm signal.

[0063] The threshold CvCmpVal may be set according to actual conditions, and is usually a small value close to zero.

[0064] By using the above-mentioned ventilator pressure sensor detection method, it is only necessary to use the detection signal to sample a small number of sample points from the pressure feedback signal through a sliding window to quickly and accurately identify whether the ventilator pressure sensor has failed. After identifying that the ventilator pressure sensor has failed, an alarm signal will be issued in time to remind the user.

[0065] Based on the above-mentioned ventilator pressure sensor detection method, the embodiment of the present invention also provides a ventilator pressure sensor detection device, see Figure 3 As shown, the device may include the following modules:

[0066] The first generating module 302 is configured to generate a detection signal corresponding to the pressure sensor based on preset signal parameters; wherein the detection signal is a discrete signal, and the preset signal parameters include amplitude, frequency, and a first sampling rate.

[0067] The second generating module 304 is configured to generate a pressure feedback signal corresponding to the pressure sensor based on a preset closed-loop transfer function, a preset target pressure value, and the detection signal.

[0068] The sampling module 306 is used to sample the pressure feedback signal at a second sampling rate through a preset sliding window to obtain pressure feedback samples corresponding to the pressure sensor in real time; wherein the size of the preset sliding window is determined based on the first sampling rate and the frequency, the second sampling rate is determined based on the frequency, and the number of pressure feedback samples obtained each time sampling is consistent with the size of the preset sliding window.

[0069] The first determination module 308 is used to determine a discrete index of the pressure feedback sample obtained in each sampling. If an abnormal event occurs in which the discrete index is less than a preset discrete index threshold, the pressure sensor is determined to have failed. The discrete index represents the degree of discreteness of the pressure feedback sample obtained in the corresponding sampling.

[0070] By using the above-mentioned ventilator pressure sensor detection device, the failure detection of the ventilator pressure sensor can be achieved by sampling the generated pressure feedback signal through a preset sliding window using the generated detection signal. The detection efficiency and accuracy are high, thereby alleviating the problem of low efficiency and accuracy of the existing ventilator pressure sensor failure detection method.

[0071] The first generation module can also be used to:

[0072] Based on the preset signal parameters, the following formula is used to generate the initial detection signal:

[0073] y=A*(1+sin(2π*Freq*(N / Fs)))

[0074] Where y is the initial detection signal, A is the amplitude, Freq is the frequency, Fs is the first sampling rate, N is the discrete sampling point number, and the length of each discrete sampling point is Fs / Freq;

[0075] The initial detection signal is converted into a continuous time domain to obtain the detection signal.

[0076] The second generating module 304 may also be used to:

[0077] Based on the preset closed-loop transfer function, the preset target pressure value and the detection signal, the pressure feedback signal is generated using the following formula:

[0078]

[0079] Wherein, Y(s) is the pressure feedback signal, U(s) is the preset target pressure value, D(s) is the detection signal, and G(s) is the preset closed-loop transfer function.

[0080] The first determination module 308 may also be configured to calculate the average and standard deviation of the pressure feedback samples obtained from each sampling, and determine the discrete index corresponding to the sampling based on the average and standard deviation corresponding to the sampling.

[0081] The above-mentioned discrete indicator may adopt a coefficient of variation; based on this, the above-mentioned first determination module 308 may also be configured to perform the following operations on the pressure feedback samples obtained by each sampling after calculating the average value and standard deviation of the pressure feedback samples obtained by the sampling:

[0082] Based on the mean and standard deviation corresponding to the sampling, the coefficient of variation corresponding to the sampling is calculated using the following formula:

[0083]

[0084] Among them, CV is the coefficient of variation, mean is the mean, and std is the standard deviation.

[0085] Based on the above Figure 3 The embodiment of the present invention also provides another ventilator pressure sensor detection device, see Figure 4 As shown, the device may also include:

[0086] The second determining module 310 is configured to determine a size of the preset sliding window based on the first sampling rate and the frequency to generate the preset sliding window.

[0087] The third determining module 312 is configured to determine the second sampling rate based on the frequency.

[0088] The second determining module 310 may also be configured to determine that the size of the preset sliding window is not less than a ratio of the first sampling rate to the frequency.

[0089] The third determining module 312 may also be configured to determine that the second sampling rate is not less than twice the frequency.

[0090] The ventilator pressure sensor detection device provided in the embodiment of the present invention has the same implementation principle and technical effects as the aforementioned ventilator pressure sensor detection method embodiment. For the sake of brief description, for matters not mentioned in the device embodiment, reference can be made to the corresponding content in the aforementioned method embodiment.

[0091] Unless otherwise specifically stated, the relative steps, numerical expressions and values ​​of the components and steps set forth in these embodiments do not limit the scope of the present invention.

[0092] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a non-volatile computer-readable storage medium that is executable by a processor. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk.

[0093] In the description of the present invention, it should be noted that the terms "center," "upper," "lower," "left," "right," "vertical," "horizontal," "inner," and "outer," etc., indicating orientations or positional relationships, are based on the orientations or positional relationships shown in the accompanying drawings and are intended solely to facilitate and simplify the description of the present invention. They are not intended to indicate or imply that the devices or components referred to must have, be constructed, or operate in a specific orientation, and therefore should not be construed as limitations on the present invention. Furthermore, the terms "first," "second," and "third" are used for descriptive purposes only and should not be construed as indicating or implying relative importance.

[0094] Finally, it should be noted that the above-described embodiments are only specific implementation methods of the present invention, which are used to illustrate the technical solutions of the present invention, rather than to limit them. The scope of protection of the present invention is not limited thereto. Although the present invention has been described in detail with reference to the above-described embodiments, those skilled in the art should understand that any person skilled in the art can modify or easily conceive of changes to the technical solutions described in the above-described embodiments within the technical scope disclosed by the present invention, or replace some of the technical features therein with equivalents. Such modifications, changes, or replacements do not deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should be included in the scope of protection of the present invention. Therefore, the scope of protection of the present invention shall be subject to the scope of protection of the claims.

Claims

1. A method for detecting a pressure sensor of a ventilator, wherein the ventilator includes a pressure sensor for real-time acquisition of a pressure signal in the airway of the ventilator, characterized in that: The method comprises: generating a detection signal corresponding to the pressure sensor based on preset signal parameters; wherein the detection signal is a discrete signal, and the preset signal parameters include amplitude, frequency, and a first sampling rate; Based on the preset closed-loop transfer function, the preset target pressure value and the detection signal, the pressure feedback signal corresponding to the pressure sensor is generated using the following formula: in, is the pressure feedback signal, is the preset target pressure value, To detect the signal, is the preset closed-loop transfer function; Sampling the pressure feedback signal at a second sampling rate through a preset sliding window to obtain pressure feedback samples corresponding to the pressure sensor in real time; wherein the size of the preset sliding window is determined based on the first sampling rate and the frequency, the second sampling rate is determined based on the frequency, and the number of pressure feedback samples obtained in each sampling is consistent with the size of the preset sliding window; Determine a discrete index of the pressure feedback sample obtained by each sampling. If an abnormal event occurs in which the discrete index is less than a preset discrete index threshold, determine that the pressure sensor has failed; wherein the discrete index represents the degree of discreteness of the pressure feedback sample obtained by the corresponding sampling.

2. The method according to claim 1, characterized in that Generating a detection signal corresponding to the pressure sensor based on preset signal parameters includes: Based on the preset signal parameters, the following formula is used to generate the initial detection signal: in, is the initial detection signal, is the amplitude, is the frequency, is the first sampling rate, is the discrete sampling point number, and the length of each discrete sampling point is ; The initial detection signal is converted into a continuous time domain to obtain the detection signal.

3. The method according to claim 1, characterized in that After generating a pressure feedback signal corresponding to the pressure sensor based on a preset closed-loop transfer function, a preset target pressure value, and the detection signal, the method further includes: determining a size of the preset sliding window based on the first sampling rate and the frequency to generate the preset sliding window; The second sampling rate is determined based on the frequency.

4. The method according to claim 3, characterized in that Determining the size of the preset sliding window based on the first sampling rate and the frequency includes: Determining that the size of the preset sliding window is not less than a ratio between the first sampling rate and the frequency; Determining the second sampling rate based on the frequency includes: The second sampling rate is determined to be no less than twice the frequency.

5. The method according to claim 1, wherein The discrete index is determined by statistics of the pressure feedback samples obtained by the corresponding sampling; Determine the discrete indicators of the pressure feedback sample obtained at each sampling, including: For the pressure feedback samples obtained by each sampling, the average value and standard deviation of the pressure feedback samples obtained by the sampling are calculated, and the discrete index corresponding to the sampling is determined based on the average value and standard deviation corresponding to the sampling.

6. The method according to claim 5, characterized in that The discrete index adopts the coefficient of variation; the discrete index corresponding to the sub-sampling is determined based on the mean value and standard deviation corresponding to the sub-sampling, including: Based on the mean and standard deviation corresponding to the sampling, the coefficient of variation corresponding to the sampling is calculated using the following formula: in, is the coefficient of variation, is the average value, is the standard deviation.

7. A ventilator pressure sensor detection device, wherein the ventilator includes a pressure sensor for real-time acquisition of the pressure signal in the ventilator airway, characterized in that: The device comprises: a first generating module, configured to generate a detection signal corresponding to the pressure sensor based on preset signal parameters; wherein the detection signal is a discrete signal, and the preset signal parameters include amplitude, frequency, and a first sampling rate; The second generating module is configured to generate a pressure feedback signal corresponding to the pressure sensor using the following formula based on a preset closed-loop transfer function, a preset target pressure value, and the detection signal: ,in, is the pressure feedback signal, is the preset target pressure value, To detect the signal, is the preset closed-loop transfer function; a sampling module, configured to sample the pressure feedback signal at a second sampling rate through a preset sliding window to obtain pressure feedback samples corresponding to the pressure sensor in real time; wherein the size of the preset sliding window is determined based on the first sampling rate and the frequency, the second sampling rate is determined based on the frequency, and the number of pressure feedback samples obtained in each sampling is consistent with the size of the preset sliding window; A determination module is configured to determine a discrete index of the pressure feedback samples obtained during each sampling operation, and to determine that the pressure sensor has failed if an abnormal event occurs in which the discrete index is less than a preset discrete index threshold. The discrete index represents the degree of discreteness of the pressure feedback samples obtained during the corresponding sampling operation.

8. The device according to claim 7, characterized in that The first generating module is further configured to: Based on the preset signal parameters, the following formula is used to generate the initial detection signal: in, is the initial detection signal, is the amplitude, is the frequency, is the first sampling rate, is the discrete sampling point number, and the length of each discrete sampling point is ; The initial detection signal is converted into a continuous time domain to obtain the detection signal.

9. The device according to claim 7, characterized in that The determining module is further configured to: For the pressure feedback samples obtained by each sampling, the average value and standard deviation of the pressure feedback samples obtained by the sampling are calculated, and the discrete index corresponding to the sampling is determined based on the average value and standard deviation corresponding to the sampling.

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