Frequency oscillation control method and system for high frequency superimposed constant frequency applied to ventilator

Abstract

The present invention discloses a frequency oscillation control method and system for high-frequency superposition of constant frequency applied to a ventilator, and relates to the technical field of medical equipment. Monitor and collect status signals of multiple ventilator users to obtain a status signal data set; calculate a first data set of lung time constants based on the status signal data set, pre-process the lung time constants, and obtain a second data set; use the second data set to determine whether there is an abnormality in the lungs; if there is an abnormality, calculate the lung acoustic spectrum, and determine whether the frequency and amplitude of the airflow are required according to the lung acoustic spectrum; on the basis of two positive pressures in the inspiratory phase and the expiratory phase, superimpose high frequency on the normal frequency ventilator used by the patient according to the measured airflow frequency and amplitude, so as to realize the superimposed high-frequency oscillation control of the ventilator. After the present invention superimposes low-amplitude high-frequency oscillation ventilation through the positive pressure ventilation mode, the ventilation airflow supplied to the patient by the ventilator has the advantages of both normal frequency positive pressure ventilation airflow and high-frequency oscillation ventilation airflow.

Description

Technical Field

[0001] The present invention relates to the technical field of medical equipment, and more specifically to a frequency oscillation control method and system for high frequency superimposed constant frequency applied to a ventilator. Background Art

[0002] In modern clinical medicine, as an effective means of artificially replacing the spontaneous ventilation function, ventilators have been widely used in respiratory failure caused by various reasons, anesthesia respiratory management during major surgery, respiratory support therapy and emergency resuscitation, and they occupy a very important position in the field of modern medicine. Ventilators are a vital medical device that can prevent and treat respiratory failure, reduce complications, and save and prolong patients' lives.

[0003] In the clinical use of ventilators, it is necessary to continuously detect the pressure in the airway in order to control the ventilation flow, frequency, pressure or amplitude of the ventilator. In the application of normal frequency positive pressure ventilation superimposed on high-frequency oscillation mode, respiratory mechanics parameters such as airway resistance, compliance and time constant are unstable, which often leads to the patient's large airway pressure being too high to be controlled, increasing the risk of injuries such as pneumothorax and mediastinal emphysema; due to factors such as airflow turbulence, temperature and inaccurate calibration of the pressure sensor itself, the accuracy of airway pressure detection results is often low. Therefore, how to solve the above technical problems is a key issue that technicians in this field urgently need to study and improve. Summary of the invention

[0004] In view of this, the present invention provides a frequency and amplitude oscillation control method and system for normal frequency positive pressure ventilation superimposed with high frequency oscillation applied to a ventilator, which superimposes high frequency on the normal frequency ventilator used by the patient based on the measured airflow frequency and amplitude on the basis of two positive pressures in the inspiratory phase and the expiratory phase, and realizes the superimposed high frequency oscillation control of the ventilator, so as to avoid the problem of high and inaccurate pressure at the patient end.

[0005] In order to achieve the above object, the present invention adopts the following technical solution:

[0006] A frequency oscillation control method for a ventilator with a high frequency superimposed on a constant frequency comprises the following steps:

[0007] Monitor and collect status signals of multiple ventilator test users to obtain a status signal data set;

[0008] Calculating a first data set of lung time constants based on the state signal data set, and obtaining a time constant of a lesion site of the patient by preprocessing to obtain a second data set;

[0009] Determine whether there is an abnormality in the lungs using the second data set; if there is an abnormality, calculate the lung acoustic spectrum, and determine whether airflow amplitude is required based on the lung acoustic spectrum;

[0010] On the basis of the two positive pressures of the inspiratory phase and the expiratory phase, combined with the airflow amplitude and time constant, high-frequency frequency and amplitude are superimposed on the normal-frequency ventilator used by the patient to achieve oscillation control of the ventilator.

[0011] Optionally, the status signal includes a heartbeat signal and a breathing signal, wherein the heartbeat signal is a carrier signal and the breathing signal is an information signal, and the information signal is superimposed on the carrier signal as the status signal.

[0012] Optionally, the information signal is superimposed on the carrier signal, and the specific steps are as follows:

[0013] Perform low-pass denoising on the carrier signal: pre-process the carrier signal and input it into a high-order low-pass filter for low-pass filtering;

[0014] Perform threshold denoising on the information signal: set the carrier signal coefficient threshold percentage and the percentage of the threshold transition window function width; use the preset carrier coefficient threshold percentage and window function to denoise the information signal;

[0015] The denoised carrier signal and information signal are superimposed using wavelet transformation to obtain a state signal.

[0016] Optionally, determining whether there is an abnormality in the lung using the second data set comprises the following steps:

[0017] Performing correlation analysis on the data in the second data set and the normal lung time constant respectively to obtain correlation analysis results;

[0018] The correlation analysis results are compared with the preset threshold of normal lung time constant, and whether there is an abnormality is determined based on the comparison results.

[0019] Optionally, the lung acoustic spectrum is calculated specifically as follows: The lung acoustic spectrum is calculated specifically as follows: At the positions of the left and right mid-clavicular lines of the patient's chest and the left and right scapular lines on the back, one is set at the upper, middle and lower positions, and one is set at the mid-sternum position, for a total of 13 acoustic sensor sites to collect acoustic data; An acoustic sensor is installed at the Y end of the patient's ventilator tube (close to the patient's side) to collect acoustic data in the airway; After Fourier transforming a single data in the first data set to be identified, the single data in the first data set to be identified after Fourier transform is filtered by a lung acoustic filter group to obtain a filtered spectrum, and then the filtered spectrum is subjected to cepstrum analysis and discrete cosine transform to obtain the lung acoustic spectrum of the single data in the first data set to be identified.

[0020] Optionally, a constant frequency is superimposed on the high-frequency ventilator used for the patient according to the airflow amplitude. Specifically, each time the amplitude of the high-frequency oscillation module increases by a set amplitude, the high-frequency oscillation module operates at the current amplitude and superimposes the constant frequency based on the operating result; when the high-frequency oscillation module operates at the current amplitude for a set time, the amplitude of the high-frequency oscillation module continues to be superimposed with the constant frequency.

[0021] A frequency oscillation control system with high frequency superimposed on constant frequency applied to a ventilator, comprising:

[0022] State signal data set acquisition module: used to monitor and collect state signals of multiple ventilator test users to obtain a state signal data set;

[0023] A lung time constant calculation module: used for calculating a first lung time constant data set based on a state signal data set, preprocessing the lung time constant, and obtaining a second data set;

[0024] Lung abnormality detection module: used to determine whether there is an abnormality in the lungs using the second data set; if there is an abnormality, the lung acoustic spectrum is calculated, and whether airflow amplitude is required according to the lung acoustic spectrum;

[0025] Ventilator oscillation control module: Based on the two positive pressures of the inspiratory phase and the expiratory phase, high frequency is superimposed on the normal frequency ventilator used by the patient according to the measured airflow frequency and amplitude, so as to realize the superimposed high-frequency oscillation control of the ventilator.

[0026] It can be seen from the above technical solutions that, compared with the prior art, the present invention provides a frequency oscillation control method and system for high frequency superposition of normal frequency applied to a ventilator. After superimposing low-amplitude high-frequency oscillation ventilation in the positive pressure ventilation mode, the ventilation airflow supplied by the ventilator to the patient has the advantages of both normal frequency positive pressure ventilation airflow and high frequency oscillation ventilation airflow. In this way, high frequency oscillation ventilation airflow is superimposed on normal frequency positive pressure ventilation, avoiding the problem of high pressure on the patient end. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying creative work.

[0028] Figure 1 It is a schematic diagram of the method of the present invention;

[0029] Figure 2 It is a schematic diagram of the structure of the present invention. DETAILED DESCRIPTION

[0030] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0031] The embodiment of the present invention discloses a frequency oscillation control method for a high frequency superimposed constant frequency applied to a ventilator, see Figure 1 , including the following steps:

[0032] Step 1, monitoring and collecting status signals of multiple ventilator test users to obtain a status signal data set;

[0033] Step 2: Calculate the first data set of lung time constants based on the state signal data set, and pre-process to obtain the time constant of the patient's lesion site to obtain the second data set;

[0034] Step 3: using the second data set to determine whether there is an abnormality in the lungs; if there is an abnormality, calculating the lung acoustic spectrum, and determining whether airflow amplitude is required according to the lung acoustic spectrum;

[0035] Step 4: On the basis of the two positive pressures of the inspiratory phase and the expiratory phase, combined with the airflow amplitude and time constant, the high-frequency frequency and amplitude are superimposed on the normal-frequency ventilator used by the patient to achieve oscillation control of the ventilator.

[0036] Further, in step 1, the state signal includes a heartbeat signal and a breathing signal, wherein the heartbeat signal is a carrier signal, the breathing signal is an information signal, and the information signal is superimposed on the carrier signal as the state signal.

[0037] Furthermore, the information signal is superimposed on the carrier signal. The specific steps are as follows:

[0038] Step 1.1, low-pass denoising of the carrier signal: pre-process the carrier signal and input it into a high-order low-pass filter for low-pass filtering;

[0039] Step 1.2, threshold denoising the information signal: setting the carrier signal coefficient threshold percentage and the percentage of the threshold transition window function width; denoising the information signal using the preset carrier coefficient threshold percentage and the window function;

[0040] Step 1.3: Superimpose the denoised carrier signal and information signal using wavelet transform to obtain a state signal.

[0041] Further, in step 3, the second data set is used to determine whether there is an abnormality in the lungs, and the steps are as follows:

[0042] Step 3.1, performing correlation analysis on the data in the second data set and the normal lung time constant respectively to obtain correlation analysis results;

[0043] Step 3.2: Compare the correlation analysis results with the preset threshold of the normal lung time constant, and determine whether there is an abnormality based on the comparison results.

[0044] Furthermore, the lung acoustic spectrum is calculated specifically as follows: The lung acoustic spectrum is calculated specifically as follows: at the positions of the left and right mid-clavicular lines of the patient's chest and the left and right scapular lines on the back, one is set at the upper, middle and lower positions, and one is set at the mid-sternum position, for a total of 13 acoustic sensor sites to collect acoustic data; an acoustic sensor is installed at the Y end of the patient's ventilator pipeline (close to the patient's side) to collect acoustic data in the airway; after Fourier transforming a single data in the first data set to be identified, the single data in the first data set to be identified after Fourier transform is filtered by a lung acoustic filter group to obtain a filtered spectrum, and then the filtered spectrum is subjected to cepstrum analysis and discrete cosine transform to obtain the lung acoustic spectrum of the single data in the first data set to be identified.

[0045] Furthermore, the process of constructing the lung acoustic filter bank is as follows: constructing a lung time constant spectrum envelope curve, and determining the center frequency of the lung acoustic filter based on the lung time constant spectrum envelope curve. The center frequency includes: for any type of sound pressure level spectrum in the N types of sound pressure level spectra, processing the any type of sound pressure level spectrum to obtain multiple cutoff frequencies corresponding to the multiple sound pressure level spectra one by one; sorting the multiple cutoff frequencies corresponding to the N types of sound pressure level spectra one by one, wherein the cutoff frequency is less than or equal to a preset threshold; screening the sorted multiple cutoff frequencies to obtain the center frequencies of a first number of filters in the lung acoustic filter group, and the first number is W; wherein the screening of the sorted multiple cutoff frequencies includes: determining whether there is repetition in the sorted multiple cutoff frequencies, and if so, deleting the repeated frequency values ​​in the multiple cutoff frequencies; taking the minimum cutoff frequency among the cutoff frequencies remaining after deleting the repeated frequency values ​​as the first center frequency of the first number of filters, finding the minimum frequency value among the cutoff frequencies larger than the first center frequency whose difference with the first center frequency is greater than or equal to 25 Hz, as the second center frequency of the first number of filters, and so on, to obtain all the center frequencies of the first number of filters.

[0046] Furthermore, in step 4, a constant frequency is superimposed on the high-frequency ventilator used by the patient according to the airflow amplitude. Specifically, each time the amplitude of the high-frequency oscillation module increases by a set amplitude, the high-frequency oscillation module operates at the current amplitude and superimposes the constant frequency based on the operating result; when the high-frequency oscillation module operates at the current amplitude for a set time, the amplitude of the high-frequency oscillation module continues to be superimposed with the constant frequency.

[0047] The present invention also has the characteristics of mucus migration in high-frequency oscillation ventilation mode:

[0048] a. Since the inhalation time is too short, the amplitude of the high-frequency oscillatory airflow decays step by step in each level of airway. The attenuation in the large airway is about 40-60%; the proximal alveoli and small airway is about 20-40%; the amplitude in the alveoli is only 10-20% of the ventilator tube end. Therefore, relatively speaking, excessive high-frequency oscillatory ventilation pressure is prone to volume injury and pressure injury to the large airway, small airway and proximal alveoli, and is safer for the distal alveoli. At the same time, in the large airway, small airway, resistance airway and proximal alveoli, a larger amplitude also means a greater pressure difference. High-frequency oscillatory ventilation presents the characteristics of asymmetric flow velocity in these parts, which is more likely to shear with the high-speed airflow during inhalation against the airway wall, and is prone to shear blistering with mucus.

[0049] b. High-frequency oscillation ventilation airflow is more likely to resonate with the inflamed parts of the lungs, and the airflow enters and exits the alveoli to displace mucus and foam with the exudate. According to the principle of high-frequency oscillation ventilation, high-frequency oscillation airflow is more likely to resonate in the inflamed parts of the lungs of pneumonia and ARDS, that is, in the parts where mucus is produced more and compliance is relatively poor, and its amplitude is larger, while in normal alveoli, resonance almost does not occur, and the amplitude is extremely small, which means that the parts of inflammatory exudate and obstruction have a larger amplitude and airflow in the high-frequency oscillation ventilation mode, thereby having better ventilation and more ventilation airflow; it also means that these alveoli are more likely to reopen and foam under the high-frequency oscillation ventilation airflow, and foam displacement occurs.

[0050] c. High-frequency oscillation ventilation is more efficient in foaming mucus in the lungs than normal-frequency positive pressure ventilation. High-frequency oscillation ventilation has a large minute ventilation volume (larger MV) and a very small tidal volume, which is often lower than the anatomical dead space; however, due to its extremely fast frequency, its minute ventilation (MV) is much larger than that of normal-frequency positive pressure ventilation; thus, the airflow through the airway conduction part and the inflamed part is relatively large, and these parts are often parts with more lung mucus, while the airflow in normal parts is relatively small. This characteristic of high-frequency oscillation ventilation is conducive to the full contact of airflow with mucus in the conduction part of the alveoli and bronchial tree, producing a large amount of foam; therefore, it has better foaming efficiency.

[0051] d. However, the more mucus foam produced by high-frequency oscillation ventilation is prone to form an air-blocking effect (Jiamin effect) at the narrow part of the airway, affecting lung ventilation. Since the inspiration and exhalation time of high-frequency oscillation ventilation is too short, the mucus foam can only reciprocate within a very short distance after being formed. When the inspiration-expiration ratio is 1:1, the migration distance is almost equal; at this time, the outward migration of foamy mucus mainly depends on volume expansion and the patient's spontaneous breathing expiratory airflow; resulting in a large number of mucus bubbles accumulating, and an air-blocking effect (i.e., Jiamin effect) occurs at the narrow part of the airway, resulting in mucus bubble obstruction, affecting the exchange of O2 and CO2, and requiring a larger pressure difference to break through; while the amplitude of high-frequency oscillation ventilation is greatly attenuated in the airways at all levels, and cannot provide a longer time and a larger pressure difference, which is not conducive to the migration of mucus bubbles over a longer distance (the principle of high-frequency oscillation ventilation and the conditions for the generation of foam, fluid mechanics derivation).

[0052] and Figure 1 Corresponding to the method shown, the present invention also discloses a frequency oscillation control system for a high frequency superimposed constant frequency applied to a ventilator for Figure 1 The implementation of the method, the specific structure is as follows Figure 2 As shown, including:

[0053] State signal data set acquisition module: used to monitor and collect state signals of multiple ventilator test users to obtain a state signal data set;

[0054] A lung time constant calculation module: used for calculating a first lung time constant data set based on a state signal data set, preprocessing the lung time constant, and obtaining a second data set;

[0055] Lung abnormality detection module: used to determine whether there is an abnormality in the lungs using the second data set; if there is an abnormality, the lung acoustic spectrum is calculated, and whether airflow amplitude is required according to the lung acoustic spectrum;

[0056] Ventilator oscillation control module: It is used to superimpose a constant frequency on the high-frequency ventilator used by the patient based on the two positive pressures of the inspiratory phase and the expiratory phase according to the airflow amplitude to achieve oscillation control of the ventilator.

[0057] In this specification, each embodiment is described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the embodiments can be referred to each other. For the device disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant parts can be referred to the method part.

[0058] The above description of the disclosed embodiments enables one skilled in the art to implement or use the present invention. Various modifications to these embodiments will be apparent to one skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to the embodiments shown herein, but rather to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A frequency oscillation control system with high frequency superimposed on constant frequency applied to a ventilator, characterized in that: include: The state signal data set acquisition module is used to monitor and collect the state signals of multiple ventilator test users to obtain a state signal data set; the state signal includes a heartbeat signal and a breathing signal, wherein the heartbeat signal is a carrier signal and the breathing signal is an information signal, and the information signal is superimposed on the carrier signal as a state signal; A lung time constant calculation module: used for calculating a first lung time constant data set based on a state signal data set, preprocessing the lung time constant, and obtaining a second data set; A lung abnormality detection module: used to determine whether there is an abnormality in the lungs using the second data set; If there is an abnormality, the lung acoustic spectrum is calculated, and whether the airflow amplitude is required is determined based on the lung acoustic spectrum; the second data set is used to determine whether there is an abnormality in the lungs. The specific steps are as follows: Performing correlation analysis on the data in the second data set and the normal lung time constant respectively to obtain correlation analysis results; Comparing the correlation analysis results with a preset threshold of a normal lung time constant, and determining whether there is an abnormality based on the comparison results; Ventilator oscillation control module: It is used to superimpose a constant frequency on the high-frequency ventilator used by the patient based on the two positive pressures of the inspiratory phase and the expiratory phase according to the airflow amplitude to achieve oscillation control of the ventilator.

2. A frequency oscillation control system with high frequency superimposed on constant frequency applied to a ventilator according to claim 1, characterized in that: The information signal is superimposed on the carrier signal. The specific steps are as follows: Perform low-pass denoising on the carrier signal: pre-process the carrier signal and input it into a high-order low-pass filter for low-pass filtering; Perform threshold denoising on the information signal: set the carrier signal coefficient threshold percentage and the percentage of the threshold transition window function width; denoise the information signal using the preset carrier signal coefficient threshold percentage and the threshold transition window function; The denoised carrier signal and information signal are superimposed using wavelet transform to obtain a state signal.

3. A frequency oscillation control system with high frequency superimposed on constant frequency applied to a ventilator according to claim 1, characterized in that: The specific steps for calculating the lung acoustic spectrum are as follows: acoustic data are collected at 13 acoustic sensor sites, one each at the upper, middle, and lower positions on the left and right clavicle midlines of the patient's chest and the left and right scapular lines on the back, and one at the mid-sternum position; an acoustic sensor is installed at the Y end of the ventilator tube near the patient to collect acoustic data in the airway; after Fourier transforming a single data in the first data set to be identified, the single data in the first data set to be identified after Fourier transform is filtered by a lung acoustic filter group to obtain a filtered spectrum, and then the filtered spectrum is subjected to cepstrum analysis and discrete cosine transform to obtain the lung acoustic spectrum of the single data in the first data set to be identified, and then the acoustic data collected at the 13 sites are compared and analyzed.

4. A frequency oscillation control system with high frequency superimposed on constant frequency applied to a ventilator according to claim 1, characterized in that: A constant frequency is superimposed on the high-frequency ventilator used for the patient according to the airflow amplitude. Specifically, each time the amplitude of the high-frequency oscillation module increases by a set amplitude, the high-frequency oscillation module operates at the current amplitude and superimposes the constant frequency based on the operating result; when the high-frequency oscillation module operates at the current amplitude for a set time, the amplitude of the high-frequency oscillation module continues to be superimposed with the constant frequency.

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