Advanced switching judgment method for respiratory support equipment

Abstract

The invention discloses a method for judging advanced switching of respiratory support equipment, which comprises the following steps of: acquiring user traffic in real time, and denoising the user traffic in real time; judging whether the user enters an expiration state or not according to the de-noised user flow, recording a timestamp of an expiration moment, and updating a flow wave crest of the user in an expiration stage and a wave trough value after a wave crest point in real time; setting a volume threshold value, calculating a difference value between the volume at the current moment and the volume at the previous moment, and judging whether the volume is changed or not according to the difference value and the volume threshold value, so as to judge whether the respiratory support equipment meets the requirement of switching the event type in advance or not. The technical problem of how to accurately and quickly identify the type of the advance switching event of the respiratory support equipment and output the result is solved.

Description

Technical Field

[0001] The present invention relates to the technical field of respiratory support equipment, and in particular to a method for determining early switching of respiratory support equipment. Background Art

[0002] In mechanical ventilation, when the user's breathing needs do not match the ventilator setting parameters, it is easy to cause human-machine asynchrony and other phenomena, resulting in poor mechanical ventilation effect and failure to achieve clinical treatment effect. Common types of human-machine asynchrony include early switching, double triggering, no triggering and false triggering. Early switching means that when the ventilator is triggered normally during inhalation, but the user's inhalation effort is still continuing, the ventilator pressure switches from IPAP to EPAP prematurely and is not triggered again. The patent document with application number 202210666276.8 discloses a method for intelligent identification and classification of ventilator-user ventilation asynchronous phenomenon, which is based on the image feature extraction model of U-Net convolutional neural network in deep learning to identify early switching. Due to the limitation of hardware resources, this solution is difficult to implement in embedded software and needs to be connected to an independent server or other platform. The method based on the previous respiratory cycle parameters requires the user to maintain a basically consistent respiratory frequency, which limits the application scenario. Therefore, it is urgent to propose a method for judging early switching of respiratory support equipment to solve the technical problem of how to accurately and quickly identify the early switching event type of respiratory support equipment and output the results. Summary of the invention

[0003] The main purpose of the present invention is to propose a method for judging early switching of respiratory support equipment, aiming to solve the technical problem of how to accurately and quickly identify the type of early switching event of respiratory support equipment and output the result.

[0004] To achieve the above object, the present invention provides a method for determining whether a respiratory support device should be switched in advance, wherein the method for determining whether a respiratory support device should be switched in advance comprises the following steps:

[0005] S1. Obtain user traffic in real time and perform real-time denoising on the user traffic;

[0006] S2. Determine whether the user has entered the exhalation state based on the denoised user traffic, record the timestamp of the exhalation moment, and update the user's traffic peak during the exhalation phase and the trough value after the peak point in real time;

[0007] S3. Set a volume threshold, calculate the difference between the volume at the current moment and the volume at the previous moment, and determine whether the volume has changed based on the difference and the volume threshold, so as to determine whether the respiratory support device meets the early switching event type.

[0008] In one of the preferred solutions, the step S1 uses FIR low-pass filtering or one-dimensional Kalman filtering to perform real-time denoising on user traffic.

[0009] In one of the preferred solutions, the step S2 determines the user flow peak during the exhalation phase, specifically:

[0010] If (Flow NUM-2 -Flow NUM-1 )*(Flow NUM-1 -Flow NUM )<0,

[0011] Flow NUM-1 -Flow NUM > 0, the flow value of the current timestamp in the exhalation phase is updated to the flow peak value; NUM-2 is the user flow value at the time of task NUM-2, Flow NUM-1 is the user flow value at the time of task NUM-1, Flow NUM It is the user flow value at task time NUM.

[0012] In one preferred solution, the step S2 determines the trough after the peak in the exhalation phase, specifically:

[0013] If (Flow NUM-2 -Flow NUM-1 )*(Flow NUM-1 -Flow NUM )<0,

[0014] Flow NUM-1 -Flow NUM <0, the flow value of the current timestamp in the exhalation phase is updated to the flow trough value, where Flow NUM-2 is the user flow value at the time of task NUM-2, Flow NUM-1 is the user flow value at the time of task NUM-1, Flow NUM It is the user flow value at task time NUM.

[0015] In one preferred solution, the step S3 sets a volume threshold, calculates the difference between the volume at the current moment and the volume at the previous moment, and determines whether the volume has changed based on the difference and the volume threshold, specifically:

[0016] Set volume thresholds;

[0017] The difference between the volume at the current moment and the volume at the previous moment is calculated. If the difference is greater than the capacity threshold, the volume waveform fluctuates during the volume decrease process of the respiratory support device.

[0018] In one of the preferred embodiments, the volume threshold is -0.05 ml or 0 ml.

[0019] In one of the preferred solutions, the step S3 determines whether the respiratory support device meets the early switching event type, including:

[0020] When the timestamp of the time when the user traffic returns to zero minus the time when the exhalation occurs is greater than the first time value, that is:

[0021] If T-Texhstart>the first time value, it is considered that the user still has inhalation efforts in the exhalation phase determined by the respiratory support device, satisfying the early switching time type; wherein T is the moment when the user flow returns to zero, and Texhstart is the timestamp of the exhalation moment.

[0022] In one of the preferred solutions, the first time value is 0.8s.

[0023] In one of the preferred solutions, the step S3 of determining whether the respiratory support device meets the early switching event type includes:

[0024] When the respiratory support device enters the inhalation moment, the peak value and trough value of the flow wave obtained during the exhalation phase are subtracted to determine whether the volume wave fluctuates. If so, it is determined that the respiratory support device belongs to the early switching time type.

[0025] One of the preferred solutions is to make a difference between the peak value and the trough value of the flow wave obtained during the exhalation phase to determine whether the volume wave fluctuates, specifically:

[0026] A flow threshold is set. If the difference between the flow peak value and the flow trough value obtained during the exhalation phase is greater than the flow threshold, it is determined that the volume wave fluctuates.

[0027] In the above technical solution of the present invention, the method for judging the early switching of the respiratory support device includes the following steps: obtaining the user flow in real time and denoising the user flow in real time; judging whether the user enters the exhalation state according to the denoised user flow, recording the timestamp of the exhalation moment, and updating the user's flow peak in the exhalation stage and the trough value after the peak point in real time; setting a volume threshold, calculating the difference between the volume at the current moment and the volume at the previous moment, and judging whether the volume has changed according to the difference and the volume threshold, so as to judge whether the respiratory support device meets the early switching event type. The present invention judges whether the respiratory support device meets the conditions for early switching by performing waveform feature decomposition on the early switching event of the respiratory support device. When the early switching event is detected, the event and time point are stored to remind medical staff to modify the non-invasive breathing related parameters, thereby solving the technical problem of how to accurately and quickly identify the early switching event type of the respiratory support device and output the results. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] 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 some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the structures shown in these drawings without paying any creative work.

[0029] Figure 1 A schematic diagram of a method for determining early switching of a respiratory support device according to an embodiment of the present invention;

[0030] Figure 2 This is a schematic diagram of a first change in user flow during the exhalation or inhalation phase of an embodiment of the present invention;

[0031] Figure 3 A second schematic diagram of changes in user flow during the exhalation or inhalation phase of an embodiment of the present invention;

[0032] Figure 4 Schematic diagram of volume change of the respiratory support device according to an embodiment of the present invention.

[0033] The realization of the purpose, functional features and advantages of the present invention will be further explained in conjunction with the implementation methods and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0034] 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.

[0035] It should be noted that all directional indications (such as up, down, etc.) in the embodiments of the present invention are only used to explain the relative position relationship, movement status, etc. between the components under a certain specific posture (as shown in the accompanying drawings). If the specific posture changes, the directional indication will also change accordingly.

[0036] In addition, in the present invention, the descriptions such as "first", "second", etc. are only used for descriptive purposes and cannot be understood as indicating or implying their relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first" or "second" may explicitly or implicitly include at least one of the features.

[0037] Furthermore, the technical solutions between the various embodiments of the present invention may be combined with each other, but this must be based on the fact that they can be implemented by ordinary technicians in the field. When the combination of technical solutions is mutually contradictory or cannot be implemented, it should be deemed that such combination of technical solutions does not exist and is not within the scope of protection required by the present invention.

[0038] See also Figure 1-Figure 4 According to one aspect of the present invention, the present invention provides a method for determining whether a respiratory support device should be switched in advance, wherein the method for determining whether a respiratory support device should be switched in advance comprises the following steps:

[0039] S1. Obtain user traffic in real time and perform real-time denoising on the user traffic;

[0040] S2. Determine whether the user has entered the exhalation state based on the denoised user traffic, record the timestamp of the exhalation moment, and update the user's traffic peak during the exhalation phase and the trough value after the peak point in real time;

[0041] S3. Set a volume threshold, calculate the difference between the volume at the current moment and the volume at the previous moment, and determine whether the volume has changed based on the difference and the volume threshold, so as to determine whether the respiratory support device meets the early switching event type.

[0042] Specifically, in this embodiment, the step S1 uses FIR low-pass filtering or one-dimensional Kalman filtering to perform real-time denoising on user traffic.

[0043] Specifically, in this embodiment, the step S2 determines the user flow peak in the exhalation phase, specifically: NUM-2 -Flow NUM-1 )*(Flow NUM-1 -Flow NUM )<0,

[0044] Flow NUM-1 -Flow NUM > 0, the flow value of the current timestamp in the exhalation phase is updated to the flow peak value; NUM-2 is the user flow value at the time of task NUM-2, Flow NUM-1 is the user flow value at the time of task NUM-1, Flow NUM It is the user flow value at task time NUM.

[0045] Specifically, in this embodiment, the step S2 determines the trough after the peak of the exhalation phase, specifically: NUM-2 -Flow NUM-1 )*(Flow NUM-1 -Flow NUM )<0,

[0046] Flow NUM-1 -Flow NUM <0, the flow value of the current timestamp in the exhalation phase is updated to the flow trough value, where Flow NUM-2 is the user flow value at the time of task NUM-2, Flow NUM-1 is the user flow value at the time of task NUM-1, Flow NUM It is the user flow value at task time NUM.

[0047] Specifically, in this embodiment, the step S3 sets a volume threshold, calculates the difference between the volume at the current moment and the volume at the previous moment, and determines whether the volume has changed according to the difference and the volume threshold, specifically: setting the volume threshold;

[0048] The difference between the volume at the current moment and the volume at the previous moment is calculated. If the difference is greater than the capacity threshold, the volume waveform fluctuates during the volume decrease process of the respiratory support device.

[0049] Specifically, in this embodiment, the volume threshold is -0.05 ml or 0 ml, which is not specifically limited in the present invention and can be set according to needs.

[0050] Specifically, in this embodiment, the step S3 determines whether the respiratory support device meets the early switching event type, including:

[0051] When the timestamp of the time when the user traffic returns to zero minus the time when the exhalation occurs is greater than the first time value, that is:

[0052] If T-Texhstart>the first time value, it is considered that the user still has inhalation efforts in the exhalation phase determined by the respiratory support device, satisfying the early switching time type; wherein T is the moment when the user flow returns to zero, and Texhstart is the timestamp of the exhalation moment.

[0053] Specifically, in this embodiment, the first time value is 0.8s, which is not specifically limited in the present invention and can be set as needed.

[0054] Specifically, in this embodiment, the step S3 determines whether the respiratory support device meets the early switching event type, including: when the respiratory support device enters the inhalation moment, the flow peak value and the flow trough value obtained in the exhalation phase are subtracted to determine whether the volume wave fluctuates. If so, it is determined that the respiratory support device belongs to the early switching time type.

[0055] Specifically, in this embodiment, the difference between the peak value and the trough value of the flow wave obtained during the exhalation phase is used to determine whether the volume wave fluctuates, specifically:

[0056] A flow threshold is set. If the difference between the flow peak value and the flow trough value obtained during the exhalation phase is greater than the flow threshold, it is determined that there is fluctuation in the volume wave. In the present invention, the flow threshold is 5 L / min, which is not specifically limited in the present invention and can be set as needed.

[0057] Specifically, in this embodiment, when the early switching time is detected, the time and time point are stored, and the medical staff is reminded to modify the parameters of the respiratory support equipment or perform other operations.

[0058] Specifically, in this embodiment, when the airway resistance and compliance are normal, after the early switching condition is met, the user's continuous inhalation maintains the user flow rate continuously greater than 0, see Figure 2 ,From the waveform properties, it can be seen that the flow rate fails to return to zero in time, a represents the user flow rate, b represents the breathing or inhalation state, the horizontal axis represents time (s), and the vertical axis represents the flow rate (L / min).

[0059] Specifically, in this embodiment, when the air resistance compliance is small, the pressure is maintained at EPAP after the early switching to exhalation. Since the tidal volume inhaled previously is not large, the user flow rate recovers to 0 quickly during the exhalation phase. The user's continuous inhalation will make the user flow rate tend to turn positive. When the inhalation effort gradually disappears, the flow rate will decrease again. This cycle will cause the user flow rate during exhalation to be blocked. See Figure 3 The horizontal axis is time (s), and the vertical axis is flow (L / min). According to the analysis of user flow, the volume waveform after the early switching event will drop rapidly, and because the inspiratory effort still exists, it will cause the flow to rise. Therefore, the volume waveform remains basically unchanged or increases for a certain period of time. Figure 4 The horizontal axis is time (s) and the vertical axis is volume (ml), which depends on the size of the inspiratory effort. When the inspiratory effort reaches a certain level, the flow rate will increase significantly, which may cause the ventilator to be triggered again, that is, the double trigger type. Invalid triggering means that the user does not trigger from beginning to end during an inspiratory effort, that is, air delivery, but there is a trigger (air delivery) process when the event is switched in advance.

[0060] The above are only preferred embodiments of the present invention, and are not intended to limit the patent scope of the present invention. All equivalent structural changes made using the contents of the present invention's specification and drawings, or directly / indirectly applied in other related technical fields, are included in the patent protection scope of the present invention.

Claims

1. A method for determining early switching of a respiratory support device, characterized in that: The following steps are involved: S1. Obtain user traffic in real time and perform real-time denoising on the user traffic; S2. Determine whether the user has entered the exhalation state based on the denoised user traffic, record the timestamp of the exhalation moment, and update the user's traffic peak during the exhalation phase and the trough value after the peak point in real time; S3. Set a volume threshold, calculate the difference between the volume at the current moment and the volume at the previous moment, and determine whether the volume has changed based on the difference and the volume threshold, so as to determine whether the respiratory support device meets the early switching event type.

2. A method for determining early switching of a respiratory support device according to claim 1, characterized in that: The step S1 uses FIR low-pass filtering or one-dimensional Kalman filtering to perform real-time denoising on user traffic.

3. A method for determining early switching of a respiratory support device according to any one of claims 1 to 2, characterized in that: The step S2 determines the user flow peak in the exhalation phase, specifically: If (Flow NUM-2 - Flow NUM-1 ) * (Flow NUM-1 - Flow NUM ) < 0, Flow NUM-1 -Flow NUM > 0, the flow value of the current timestamp in the exhalation phase is updated to the flow peak value; NUM-2 is the user flow value at the time of task NUM-2, Flow NUM-1 is the user flow value at the time of task NUM-1, Flow NUM It is the user flow value at task time NUM.

4. A method for determining early switching of a respiratory support device according to any one of claims 1 to 2, characterized in that: The step S2 determines the trough after the peak in the exhalation phase, specifically: If (Flow NUM-2 - Flow NUM-1 ) * (Flow NUM-1 - Flow NUM ) < 0, Flow NUM-1 -Flow NUM <0, the flow value of the current timestamp in the exhalation phase is updated to the flow trough value, where Flow NUM-2 is the user flow value at the time of task NUM-2, Flow NUM-1 is the user flow value at the time of task NUM-1, Flow NUM It is the user flow value at task time NUM.

5. A method for determining early switching of a respiratory support device according to any one of claims 1 to 2, characterized in that: The step S3 sets a volume threshold, calculates the difference between the volume at the current moment and the volume at the previous moment, and determines whether the volume has changed based on the difference and the volume threshold, specifically: Set volume thresholds; The difference between the volume at the current moment and the volume at the previous moment is calculated. If the difference is greater than the capacity threshold, the volume waveform fluctuates during the volume decrease process of the respiratory support device.

6. A method for determining early switching of a respiratory support device according to claim 5, characterized in that: The volume threshold is -0.05 ml or 0 ml.

7. A method for determining early switching of a respiratory support device according to any one of claims 1 to 2, characterized in that: The step S3 determines whether the respiratory support device meets the early switching event type, including: When the timestamp of the time when the user traffic returns to zero minus the time when the exhalation occurs is greater than the first time value, that is: If T-Texhstart>the first time value, it is considered that the user still has inhalation efforts in the exhalation phase determined by the respiratory support device, satisfying the early switching time type; wherein T is the moment when the user flow returns to zero, and Texhstart is the timestamp of the exhalation moment.

8. A method for determining early switching of a respiratory support device according to claim 7, characterized in that: The first time value is 0.8s.

9. A method for determining early switching of a respiratory support device according to any one of claims 1 to 2, characterized in that: The step S3 determines whether the respiratory support device meets the early switching event type, including: When the respiratory support device enters the inhalation moment, the peak value and trough value of the flow wave obtained during the exhalation phase are subtracted to determine whether the volume wave fluctuates. If so, it is determined that the respiratory support device belongs to the early switching time type.

10. A method for determining early switching of a respiratory support device according to claim 9, characterized in that: The difference between the peak value and the trough value of the flow wave obtained during the exhalation phase is used to determine whether the volume wave fluctuates, specifically: A flow threshold is set. If the difference between the flow peak value and the flow trough value obtained during the exhalation phase is greater than the flow threshold, it is determined that the volume wave fluctuates.

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