An airway secretion accumulation detection method based on invasive respirator flow waveform and respirator

Abstract

The present application belongs to the technical field of medical devices, and particularly relates to a method for detecting airway secretion accumulation based on invasive respirator flow waveform and a respirator. n The method comprises the following steps: step 1) obtaining a sampling point X of the invasive respirator flow signal at the nth moment n ; step 2) performing real-time normalization processing and band-pass digital filtering on the sampling value, and calculating the average power P of the filtered signal at the nth moment n ; step 3) when n does not reach the set number of sampling points, n is increased by 1, and the process returns to step 1); otherwise, the process returns to step 4); step 4) determining whether P is lower than a preset threshold value, and if yes, the airway is normal; otherwise, the airway has accumulated secretion. The method of the present application is not constrained by ventilation mode and ventilation parameter setting, and can be used for various invasive mechanical ventilation; has extremely low spatial complexity, occupies few CPU resources; has low requirement for operators, and is accurate and reliable in judging the secretion in the airway.

Description

Technical Field

[0001] This invention belongs to the field of medical device technology, and in particular relates to a method for detecting airway secretion accumulation based on the flow waveform of an invasive ventilator and a ventilator. Background Technology

[0002] In patients receiving prolonged invasive mechanical ventilation, airway secretions gradually accumulate, leading to airway obstruction, coughing, and increased airway pressure. Besides increasing the risks associated with mechanical ventilation, excessive secretion accumulation can also cause secondary lung infections. Therefore, tubing suction is one of the most common nursing procedures in intensive care. Nurses use specific negative pressure devices and narrow-diameter endotracheal tubes to suction secretions from the airway or the inner walls of the tubing, maintaining airway patency. This procedure is often performed periodically in clinical practice, approximately every two hours. For patients with lung infections and excessive sputum, this nursing process helps reduce the risk of airway obstruction; however, for patients with dry airways and little sputum, frequent tubing suction is undoubtedly a painful experience and detrimental to recovery. Currently, on-demand suctioning is becoming a consensus in clinical nursing, requiring nurses to have a thorough understanding of the patient's condition and be able to correctly interpret the relationship between various monitoring parameters and airway secretion accumulation. However, this relies heavily on the experience of the operator. Therefore, a detection method is needed in clinical practice to help detect the accumulation of secretions in the airway. When the accumulation reaches a certain level, it should prompt nursing staff to perform tubing suction to ensure that sputum is suctioned as needed. This is of great significance for reducing the risks of mechanical ventilation and improving the user's treatment experience.

[0003] When fluid accumulates in the tubing or the user's airway, the airway pressure and flow rate waveforms exhibit significantly different characteristics compared to normal conditions. This is one of the criteria used clinically to determine the timing of suctioning. Therefore, analyzing and calculating the characteristics of the pressure and flow rate waveform signals could serve as a method for automatically detecting the accumulation of airway secretions. In fact, no ventilator currently on the market possesses a similar function.

[0004] Currently, products with similar functions on the market are generally specific devices independent of ventilators. The technical approach they use is to use the calculation and analysis results of breath sound signals to indicate whether the user needs suctioning. These products require the installation of electronic auscultation probes to continuously monitor breath sounds, which is inconvenient to use, easily affected by environmental noise, and these monitoring devices are expensive. They are not a necessary option in intensive care scenarios at this stage, so they have not been widely used in clinical practice. Summary of the Invention

[0005] The purpose of this invention is to overcome the defects of the prior art and to propose a method for detecting airway secretion accumulation based on the flow waveform of an invasive ventilator and a ventilator.

[0006] To achieve the above technical objectives, this invention proposes a method for detecting airway secretion accumulation based on invasive ventilator flow waveforms, comprising: Step 1) Acquire invasive ventilator flow signal n sampling points at time ; Step 2) Normalize the sampled values ​​in real time, apply bandpass digital filtering, and calculate the first... n Average power of the filtered signal at any time P n ; Step 3) When n If the set number of sampling points has not been reached, n (Increase by 1 and proceed to step 1); otherwise, proceed to step 4). Step 4) Determine P n If the airway is below a preset threshold, it is considered normal; otherwise, airway secretions accumulate.

[0007] Preferably, step 2) includes: Obtained through recursion The mean and variance; calculate normalized boundary U n ; According to the boundary U n right Perform normalization and amplitude limiting; The signal after amplitude limiting is then subjected to bandpass digital filtering to obtain the first... n The filtering result at time; The corresponding average power is obtained through a recursive method. P n .

[0008] Preferably, the method of obtaining through recursion is... The mean and variance; including: According to the invasive ventilator flow signal n -1 sampling point X n-1 mean E n-1 ,variance The result is obtained by recursion. mean ,variance for:

[0009] .

[0010] Preferably, the normalized boundary U n for: U n =[ R 1n , R 2n ],in,

[0011] .

[0012] Preferably, the boundary U n right Normalization and amplitude limiting are performed, including: judge X n Does it exceed the range? U n If the boundary is exceeded, it is set to... U n boundary values R 1n or R 2n ; Normalization is performed according to the following formula to obtain the normalized result. for: .

[0013] Preferably, the bandpass digital filter z Domain transfer function for:

[0014] Among them, the coefficients of the numerator and denominator b 0 ,…, b p , a 0 ,…, a p All are known quantities, the first n Filtering results at time 1 Y n for:

[0015] in, p and q These are the feedforward and feedback orders of the digital filter, respectively.

[0016] Preferably, the first n Average power at timeP n for:

[0017] in, For the first n Average power at time -1.

[0018] Secondly, the present invention provides an airway secretion accumulation detection module based on the invasive ventilator flow waveform, wherein the detection module implements the steps of the above method.

[0019] On the other hand, the present invention provides an invasive ventilator that employs the above-mentioned detection module.

[0020] Compared with the prior art, the advantages of the present invention are: 1. This invention is a signal processing algorithm based on the flow waveform of an invasive ventilator. It can analyze abnormal oscillation characteristics of the flow signal in real time, thereby identifying the accumulation status of airway secretions and providing early warning of airway secretion accumulation events during mechanical ventilation. This invention can be used in invasive ventilators as a monitoring parameter or software function. 2. This method is based on real-time monitoring of ventilator flow waveform and can be embedded into the ventilator as software without the need for third-party equipment or additional sensors. 3. This method is not restricted by ventilation mode or ventilation parameter settings and can be used for various invasive mechanical ventilations; 4. This method has extremely low space complexity and consumes little CPU resources; 5. This method requires minimal operator skill and provides accurate and reliable assessment of airway secretions. Attached Figure Description

[0021] Figure 1 This is a flowchart of the airway secretion accumulation detection method of the present invention; Figure 2 These are box plots showing the calculation results for two sets of test samples. Detailed Implementation

[0022] The technical solution of the present invention will be described in detail below with reference to the accompanying drawings and embodiments.

[0023] Example Embodiments of the present invention provide a method for detecting airway secretion accumulation based on invasive ventilator flow waveform, comprising: Step 1) Acquire invasive ventilator flow signal n sampling points at time ; Step 2) Normalize the sampled values ​​in real time, apply bandpass digital filtering, and calculate the first...n Average power of the filtered signal at any time P n ; Step 3) When n If the set number of sampling points has not been reached, n (Increase by 1 and proceed to step 1); otherwise, proceed to step 4). Step 4) Determine P n If the airway is below a preset threshold, it is considered normal; otherwise, airway secretions accumulate.

[0024] like Figure 1 As shown, this is achieved through the following steps: 1. Obtain the first n Time and the n A sampling point of the ventilator's flow waveform signal at time -1 is denoted as... X n and X n-1 ,in n It is a positive integer.

[0025] 2. Remember the first n Time and the n The mean values ​​of the flow signal at time -1 are respectively: E n and E n-1 Calculated using the following recursive formula E n Value:

[0026] 3. Record the first n Time and the n- The variances of the flow signals at time 1 are respectively and Calculated using the following recursive formula Value:

[0027] 4. Calculation X n The maximum distributable interval, U n =[ R 1n , R 2n ],in:

[0028]

[0029] 5. JudgmentX n Does it exceed the range? U n If the boundary is exceeded, it is set to... U n boundary values R 1n or R 2n .

[0030] 6. To X n In the interval U n Perform normalization internally, and denote the normalized result as... ,but:

[0031] 7. For the normalized X n Bandpass digital filtering utilizes digital filters of the following forms. z Domain transfer function:

[0032] Where the coefficients of the numerator and denominator b 0 ,…, b p , a 0 ,…, a p All of these are known quantities obtained during filter design, and the filtering result is a band-limited signal within a certain frequency range. n Filtering results at time 1 Y n Calculated by the following formula:

[0033] 8. Calculate the band-limited signal at the current time. Y n power P n It is given by the following recurrence relation:

[0034] 9. A check is performed at regular intervals, which in one embodiment can be 10-30 seconds. P n Does it exceed the preset threshold? h If the value exceeds a certain threshold, it indicates that the abnormal oscillation component caused by the accumulation of airway secretions accounts for a high proportion of the current flow signal, and the current ventilation status is determined to be airway secretion accumulation; otherwise, it indicates that the flow signal is normal.

[0035] In one embodiment, the present invention provides an airway secretion accumulation detection module based on the invasive ventilator flow waveform, the detection module implementing the steps of the above method.

[0036] In another embodiment, the present invention provides an invasive ventilator that employs the above-described detection module.

[0037] Figure 2 This is a controlled experiment conducted using the method of the present invention on real clinical data. The experimental group included 243 flow waveform signals monitored by the ventilator under sputum accumulation, and the control group included 246 flow waveform signals under normal conditions. The duration of each sample signal was 30 seconds. The distribution of the band-limited signal power calculated by this method is shown in the figure.

[0038] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to the embodiments, those skilled in the art should understand that modifications or equivalent substitutions to the technical solutions of the present invention do not depart from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A method for detecting airway secretion accumulation based on invasive ventilator flow waveform, comprising: Step 1) Acquire invasive ventilator flow signal n sampling points at time ; Step 2) Normalize the sampled values ​​in real time, apply bandpass digital filtering, and calculate the first... n Average power of the filtered signal at any time P n ; Step 3) When n If the set number of sampling points has not been reached, n Increase by 1 and proceed to step 1). Otherwise, proceed to step 4). Step 4) Determine P n If the airway is below a preset threshold, and the result is yes, the airway is normal. Otherwise, airway secretions will accumulate; Step 2) includes: Obtained through recursion The mean and variance; calculate normalized boundary U n ; According to the boundary U n right Perform normalization and amplitude limiting; The signal after amplitude limiting is then subjected to bandpass digital filtering to obtain the first... n The filtering result at time; The corresponding average power is obtained through a recursive method. .

2. The method for detecting airway secretion accumulation based on invasive ventilator flow waveform according to claim 1, characterized in that, The method obtained through recursion The mean and variance; including: According to the invasive ventilator flow signal n -1 sampling point X n-1 mean E n-1 ,variance The result is obtained by recursion. mean ,variance for: 。 3. The method for detecting airway secretion accumulation based on invasive ventilator flow waveform according to claim 2, characterized in that, The normalized boundary U n for: U n =[ R 1n , R 2n ],in, 。 4. The method for detecting airway secretion accumulation based on invasive ventilator flow waveform according to claim 3, characterized in that, According to the boundary U n right Perform normalization and amplitude limiting; include: judge X n Does it exceed the range? U n If the boundary is exceeded, it is set to... U n boundary values R 1n or R 2n ; Normalization is performed according to the following formula to obtain the normalized result. for: 。 5. The method for detecting airway secretion accumulation based on invasive ventilator flow waveform according to claim 4, characterized in that, The bandpass digital filter z Domain transfer function for: Among them, the coefficients of the numerator and denominator b 0 ,…, b p , a 0 ,…, a p All are known quantities, the first n Filtering results at time 1 Y n for: in, p and q These are the feedforward and feedback orders of the digital filter, respectively.

6. The method for detecting airway secretion accumulation based on invasive ventilator flow waveform according to claim 5, characterized in that, The first n Average power at time P n for: in, For the first n Average power at time -1.

7. A module for detecting airway secretion accumulation based on invasive ventilator flow waveform, characterized in that, The detection module implements the steps of the method according to any one of claims 1-6.

8. An invasive ventilator, characterized in that, The ventilator uses the detection module as described in claim 7.

Images