Method and device for measuring lung overinflation coefficient, equipment, storage medium

Abstract

The present application is suitable for the technical field of medical devices, and provides a lung overexpansion coefficient calculation method, device, equipment and storage medium. The airway pressure value and airway real-time flow rate of a patient are collected, the real-time compliance pressure and lung real-time volume are obtained according to the airway pressure value and airway real-time flow rate, the real-time compliance pressure and real-time volume are functionally fitted to generate a first fitting function and a second fitting function, and finally, the lung overexpansion coefficient value is calculated and output according to the first fitting function and the second fitting function and the effective inspiration time in any breathing cycle. The present application can calculate the lung overexpansion coefficient of a patient by storing the parameter group information of the fitting function, without storing all real-time data collected by the sensor, thereby reducing the data storage burden, effectively avoiding the problems of insufficient memory or system task timeout caused by large data storage, and making it impossible to calculate the lung overexpansion coefficient.

Description

Technical Field

[0001] This invention belongs to the field of medical devices, and in particular relates to a method, device, equipment, and storage medium for calculating the lung overinflation coefficient. Background Technology

[0002] Human respiration refers to the periodic and rhythmic inhalation and exhalation of air to achieve gas exchange. For some patients who cannot breathe independently, mechanical ventilation can help them complete their breathing. Currently, ventilators, as an effective means of artificially replacing spontaneous ventilation, are widely used in respiratory failure caused by various reasons, anesthetic respiratory management, respiratory support therapy, and emergency resuscitation. During mechanical ventilation, improper ventilation parameters can damage the patient's lungs. Therefore, it is necessary to monitor the patient's lung function indicators in real time. Among these, the lung overinflation coefficient is one of the important indicators for lung function monitoring.

[0003] The lung overinflation coefficient is the ratio of compliance during the last 20% of the inspiratory phase to the overall compliance during the entire inspiratory phase. In non-constant flow conditions, patient resistance pressure varies with flow rate, requiring the acquisition of volume and pressure at each time point to calculate compliance. However, in reality, compliance cannot be calculated during inspiratory time without a flow rate setting, as this is not considered effective inspiratory time. Under pressure-controlled breathing, flow rate changes are determined by factors such as patient resistance and compliance, making it impossible to accurately predict the arrival of the last 20% of the inspiratory phase. Therefore, the real-time volume and pressure values ​​corresponding to this time point cannot be directly output. Existing technology calculates the lung overinflation coefficient by storing data for the entire inspiratory phase and then querying the pressure and volume values ​​for the last 20% of the inspiratory phase after the inspiratory phase ends.

[0004] Because existing technologies require storing all data from the entire inhalation phase to obtain the lung overinflation coefficient, the amount of data that needs to be stored is too large, which can easily lead to insufficient memory or system task timeouts, resulting in the inability to calculate the lung overinflation coefficient due to missing data. Summary of the Invention

[0005] This invention provides a method for calculating the lung overinflation coefficient, aiming to solve the technical problem that current ventilators in non-constant flow mode need to store all data of the entire inspiratory phase to obtain the lung overinflation coefficient index, resulting in excessive data storage.

[0006] To address the aforementioned technical problems, in a first aspect, embodiments of the present invention provide a method for calculating the lung overinflation coefficient, comprising:

[0007] Collect the patient's airway pressure and real-time airway flow rate;

[0008] Based on the airway pressure value and the real-time airway flow rate, obtain the real-time compliance pressure and the real-time lung volume;

[0009] The real-time compliant pressure and the real-time volume are respectively fitted by functions to generate a first fitting function and a second fitting function;

[0010] The lung overinflation coefficient value is calculated and output based on the first fitting function, the second fitting function, and the effective inspiratory time within any respiratory cycle.

[0011] Furthermore, the step of performing function fitting on the real-time compliance pressure and the real-time volume respectively is specifically as follows:

[0012] The starting point for initializing the function fitting is set, and the flow rate threshold is set. The real-time flow rate of the airway is compared with the flow rate threshold to determine whether the inhalation phase has ended.

[0013] If the real-time flow rate of the airway is greater than the flow rate threshold, then the function fitting continues;

[0014] If the real-time flow rate of the airway is less than or equal to the flow rate threshold, then function fitting is stopped.

[0015] Furthermore, the starting point for the function fitting is set to a first value, and the function fitting begins when the airway pressure value rises to the first value.

[0016] Furthermore, when performing function fitting on the real-time compliant pressure and the real-time volume respectively, the values ​​of the parameter set required for function fitting are calculated using the least squares method.

[0017] Furthermore, when performing function fitting on the real-time compliant pressure and the real-time volume, a quadratic or cubic function is used for fitting.

[0018] Furthermore, the step of obtaining real-time compliance pressure specifically includes:

[0019] The compensation resistance is obtained based on the airway pressure value and the real-time airway flow rate;

[0020] The real-time compliance pressure is calculated based on the compensation resistance.

[0021] Secondly, the present invention also provides a device for measuring the lung overexpansion coefficient under non-constant flow conditions, comprising:

[0022] The acquisition unit is used to collect the patient's airway pressure and real-time airway flow rate;

[0023] The first calculation unit is used to obtain the real-time compliance pressure and the real-time lung volume based on the airway pressure value and the real-time airway flow rate.

[0024] The second calculation unit is used to perform function fitting on the real-time compliance pressure and the real-time volume respectively, and generate a first fitting function and a second fitting function.

[0025] The third calculation unit is used to calculate and output the lung overinflation coefficient value based on the first fitting function and the second fitting function, as well as the effective inspiratory time within any respiratory cycle.

[0026] Thirdly, the present invention also provides a ventilator, comprising:

[0027] Sensors are used to collect patients' airway pressure and real-time airway flow rate;

[0028] One or more processors, working individually or collectively, are used to perform the following steps:

[0029] Based on the airway pressure value and the real-time airway flow rate, obtain the real-time compliance pressure and the real-time lung volume;

[0030] The real-time compliant pressure and the real-time volume are respectively fitted by functions to generate a first fitting function and a second fitting function;

[0031] Based on the first fitting function and the second fitting function, and the effective inspiratory time within any respiratory cycle, calculate and output the lung overinflation coefficient value;

[0032] as well as

[0033] A memory used to store data.

[0034] Fourthly, the present invention also provides a computer-readable storage medium storing program instructions that, when executed by a processor, implement the steps of the lung overinflation coefficient calculation method according to any one of claims 1 to 7.

[0035] This invention effectively represents real-time compliance pressure and real-time volume by storing the parameter sets of the generated first and second fitting functions, thereby calculating and outputting the patient's lung overinflation coefficient index. It eliminates the need to store all real-time data collected by the sensors, reducing the data storage burden and effectively avoiding the problem of insufficient memory or system task timeouts caused by large data storage, which would prevent the calculation of the lung overinflation coefficient. Attached Figure Description

[0036] To more clearly illustrate the solutions in this invention, the accompanying drawings used in the description of the embodiments of this invention will be briefly introduced below. Obviously, the drawings described below are some embodiments of this invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0037] Figure 1 This is a flowchart of an embodiment of the lung overinflation coefficient calculation method provided by the present invention;

[0038] Figure 2 This is a flowchart of a specific implementation of the function fitting process provided by the present invention;

[0039] Figure 3 This is a flowchart of another specific embodiment of the lung overinflation coefficient calculation method provided by the present invention;

[0040] Figure 4 This is a flowchart of a specific implementation method for obtaining real-time compliance pressure and real-time lung volume provided by the present invention;

[0041] Figure 5 This is a schematic diagram of the lung overinflation coefficient measuring device provided by the present invention;

[0042] Figure 6 This is a schematic diagram of the lung overinflation coefficient measurement system provided by the present invention. Detailed Implementation

[0043] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains; the terminology used herein in the specification is for the purpose of describing particular embodiments only and is not intended to limit the invention; the terms "comprising" and "having," and any variations thereof, in the specification, claims, and foregoing drawings are intended to cover non-exclusive inclusion. The terms "first," "second," etc., in the specification, claims, or foregoing drawings are used to distinguish different objects and not to describe a particular order.

[0044] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of the invention. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0045] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0046] To facilitate understanding of the technical terms used in this field, the following explanations are provided.

[0047] Mechanical ventilation: It is a ventilation method that uses a ventilator to establish a pressure difference between the airway opening and the alveoli to provide respiratory support to patients with respiratory failure. It uses mechanical devices to replace, control or change spontaneous breathing movements.

[0048] Lung compliance: The change in lung volume caused by a change in unit pressure.

[0049] Considering that the data sets of pressure and volume collected in reality are relatively smooth and regular curves, this embodiment of the invention adopts a method of function fitting to the real-time compliant pressure and volume to reduce the pressure on the chip storage.

[0050] As an effective means of artificially replacing spontaneous ventilation, ventilators are widely used in modern clinical medicine. They are devices that can replace, control, or alter normal physiological breathing, increase lung ventilation, improve respiratory function, reduce respiratory work consumption, and conserve cardiac reserve. While medical staff generally follow cardiopulmonary guidelines for mechanical ventilation, setting typical tidal volumes of 500 ml and respiratory rates of 10-12 breaths / min, this setup still cannot completely prevent overventilation depending on the individual patient's lung function.

[0051] In clinical practice, doctors assess a patient's respiratory status under mechanical ventilation by using real-time data and various pulmonary function indicators displayed on the ventilator's monitor. The lung overexpansion coefficient (LEC) represents the change in compliance during the late inspiratory phase. Normally, late inspiratory compliance should remain constant; a decrease in late inspiratory compliance suggests possible lung overventilation, while an increase suggests possible lung recruitment. Therefore, as a crucial indicator for pulmonary function monitoring, the LEC data must be validated and accurate.

[0052] Example 1

[0053] Please see Figure 1 This invention provides a method for calculating the lung overinflation coefficient, comprising:

[0054] In step S1, the patient's airway pressure and real-time airway flow rate are collected;

[0055] It is understood that, in the embodiments of the present invention, during the process of breathing using a mechanical ventilation device, the pressure value and real-time flow rate of the patient's airway are collected by the sensor group on the mechanical ventilation device.

[0056] Understandably, the sensor array includes at least a flow rate sensor and a proximal pressure sensor. The flow rate sensor is used to collect the real-time flow rate in the patient's airway, and the proximal pressure sensor is used to collect the real-time pressure value in the patient's airway.

[0057] In step S2, real-time compliance pressure and real-time lung volume are obtained based on airway pressure value and real-time airway flow rate;

[0058] Understandably, during mechanical ventilation, the patient's respiratory mechanics affects lung compliance (such as airway resistance) under different ventilation modes. Specifically, in pressure-controlled ventilation (PCV) mode, the patient's airway resistance pressure changes with the flow rate due to the non-constant flow rate.

[0059] In some implementations, the influence of airway resistance is ignored, and the real-time compliance pressure is simply obtained by using the airway pressure value. The real-time airway flow rate is integrated over a preset unit time or over a respiratory cycle to directly obtain the real-time compliance pressure and the real-time lung volume. This method generally results in a large error in the calculation results.

[0060] In other implementations, taking into account the influence of airway resistance, the airway pressure value is compensated for to a certain extent before obtaining the real-time compliance pressure. The real-time airway flow rate is then integrated over a preset unit time or over a respiratory cycle to obtain the real-time lung volume.

[0061] In step S3, a function is fitted to the real-time compliance pressure and the real-time volume to generate a first fitting function and a second fitting function;

[0062] In practice, after obtaining the correspondence between real-time compliance pressure and real-time lung volume over time, functions are fitted to both relationships to calculate the real-time compliance pressure and real-time lung volume at any given time. The specific process includes: selecting appropriate parametric function expressions to represent the relationships between real-time compliance pressure and real-time lung volume, calculating the parameter values ​​that best approximate the actual collected data, and substituting these parameter values ​​into the function expressions to generate a first fitting function and a second fitting function. The first fitting function represents the relationship between real-time compliance pressure and time, and the second fitting function represents the relationship between real-time lung volume and time.

[0063] Specifically, in this embodiment, there are various ways to implement function fitting, such as least squares method, polynomial fitting, neural network, Levenberg-Marquardt algorithm, etc.

[0064] In step S4, the lung overinflation coefficient value is calculated and output based on the first fitting function, the second fitting function, and the effective inspiratory time within any respiratory cycle.

[0065] Specifically, in this embodiment, the time it takes for the flow rate to drop to zero varies depending on the lung compliance of different patients within any respiratory cycle. Higher lung compliance results in a longer period of flow, while lower lung compliance results in a shorter period. Therefore, it is impossible to predict the end of the flow in advance. In this embodiment, the time corresponding to 20% of the final flow rate is selected as the end of the effective inspiratory time t. Of course, the end time of the effective inspiratory time can be selected according to different needs, scenarios, or specific circumstances, or by adopting other methods.

[0066] Specifically, in this embodiment, time is substituted into the first fitting function and the second fitting function to calculate the pressure and volume values ​​corresponding to the effective inhalation start time, 80% t time and the effective inhalation end time within the effective inhalation time period, respectively. Finally, the ratio of the compliance C20 for the last 20% of the effective inhalation time to the compliance C for the entire inhalation phase is obtained according to the compliance formula.

[0067] In the method for calculating the lung overinflation coefficient under non-constant flow conditions, this invention performs function fitting on real-time compliance pressure and real-time volume to generate a first fitting function and a second fitting function, and stores the parameter set of the fitting function. This eliminates the need to store all the real-time data collected by the sensor, effectively representing the real-time compliance pressure and real-time volume, thereby calculating and outputting the patient's lung overinflation coefficient index. This reduces the data storage burden and effectively prevents the problem of insufficient memory or system task timeouts that prevent the calculation of the lung overinflation coefficient.

[0068] Example 2

[0069] Further, please refer to Figure 2 , Figure 2 This is a flowchart of a specific implementation of the function fitting process provided by the present invention. Step S3 specifically includes:

[0070] In step S31, the starting point of the function fitting is initialized, and the flow rate threshold is set. The real-time airway flow rate is compared with the flow rate threshold to determine whether the inhalation phase has ended.

[0071] Specifically, in this embodiment, in PCV mode, the starting point of the function fitting is first initialized. The initialization includes setting the volume of the starting point of the function fitting to zero, and the pressure value of the starting point is the pressure value P0 monitored by the lower computer. The pressure value P0 is the end-expiratory pressure set by the doctor according to the patient's actual situation.

[0072] Specifically, in this embodiment, since the changes in volume and pressure are also close to zero when the flow rate is close to zero, it is meaningless to solve for lung compliance at this time. Therefore, a flow rate threshold is actually set to determine whether the inspiratory phase has ended. When the result is that the inspiratory phase has not ended, the function fitting continues. When the result is that the inspiratory phase has ended, the function fitting stops.

[0073] In step S32, if the real-time airway flow rate is greater than the flow rate threshold, then the function fitting continues.

[0074] In this specific embodiment, the flow rate threshold is set to 2 L / min, but different values ​​can be set depending on the specific circumstances; no specific limitation is made here. The real-time airway flow rate collected by the flow sensor is compared to whether it is greater than 2 L / min. If the real-time airway flow rate is greater than 2 L / min, the inspiratory phase has not ended, and function fitting continues.

[0075] In step S33, if the real-time airway flow rate is less than or equal to the flow rate threshold, then the function fitting is stopped.

[0076] In a specific embodiment, if the real-time airway flow rate is less than or equal to 2 L / min, the inhalation phase ends and function fitting stops.

[0077] By setting a flow rate threshold, the time period during the inspiratory phase that has no practical significance for the function fitting process can be removed. This avoids the situation where the tidal volume and pressure changes are both 0 in the later stages of inspiratory phase, and the numerator and denominator of compliance are both 0, which would lead to the calculation of meaningless C20, thus improving the accuracy of function fitting.

[0078] Example 3

[0079] Furthermore, another specific implementation of the function fitting process provided by the present invention, Example 3, differs from Example 2 in that the pressure value at the starting point of function fitting in step S31 is set to a first value, and function fitting begins when the airway pressure value rises to the first value.

[0080] Specifically, in this embodiment, the first value is a set airway pressure threshold. If the pressure value of the patient's airway collected by the proximal pressure sensor is less than the airway pressure threshold, the system continues to wait. When the pressure value of the patient's airway collected by the proximal pressure sensor rises to the airway pressure threshold, function fitting begins.

[0081] Specifically, in this embodiment, during the function fitting process, as shown by the Taylor expansion, shortening the fitting time can effectively improve the accuracy of the function fitting. In this embodiment, the first value is set to pressure value P2, where pressure value P2 is 50% of the pressure value P1 monitored by the lower-level machine, and pressure value P1 is the inspiratory pressure value set by the doctor based on the patient's actual condition. Different values ​​can also be set as the starting point for function fitting depending on the specific situation; no specific limitation is made here.

[0082] Specifically, when the pressure value collected by the proximal pressure sensor in the patient's airway rises to pressure value P2, function fitting begins.

[0083] By setting the starting point for function fitting, the distance between the fitting start point and the C20 time point can be further shortened, thereby improving the accuracy of function fitting and making the calculation of the lung overinflation coefficient more accurate.

[0084] Example 4

[0085] Further, please refer to Figure 3 , Figure 3 This is a flowchart of another specific embodiment of the lung overinflation coefficient calculation method provided by the present invention. The difference from Embodiment 1 is that step S3 further adopts the method of step S3' for function fitting, specifically:

[0086] When performing function fitting on real-time compliant pressure and real-time volume, the values ​​of the parameter set required for function fitting are calculated using the least squares method.

[0087] Specifically, in this embodiment, after obtaining the correspondence between real-time compliance pressure and real-time lung volume over time, function fitting is performed on the relationship between real-time compliance pressure and time and the relationship between real-time lung volume and time, respectively. The real-time compliance pressure and real-time lung volume at any given time are calculated through function fitting. The specific process includes: selecting a quadratic or cubic function to represent the relationship between real-time compliance pressure and time and the relationship between real-time lung volume and time. In selecting the function order, a higher order function expression contains richer detailed information and more accurate estimates, but also involves greater computational load. In this embodiment, a quadratic function expression is used to set the parameter set, and function fitting is performed using the least squares method. The parameter values ​​closest to the actual collected data are calculated. Substituting the parameter values ​​into the function expression generates a first fitting function and a second fitting function, where the first fitting function represents the relationship between real-time compliance pressure and time, and the second fitting function represents the relationship between real-time lung volume and time.

[0088] Specifically, in this embodiment, a quadratic function is used to represent the relationship between real-time compliance pressure and time and the relationship between real-time lung volume and time. The fitting equation for real-time compliance pressure and real-time lung volume using a quadratic function is as follows:

[0089] P C =a1t 2 +b1t+c1,

[0090] Vol=a2t 2 +b2t+c2,

[0091] Among them, P C For real-time compliant pressure, Vol is the real-time volume, and a1, b1, c1, a2, b2, and c2 are the fitting parameter set.

[0092] Function fitting using the least squares method requires only two sets of parameters when using a quadratic function. This reduces the computational load of the function fitting process while still meeting the required fitting accuracy. Additionally, it reduces the number of parameter sets that need to be stored, thus alleviating the data storage burden.

[0093] Example 5

[0094] Further, please refer to Figure 4 , Figure 4 This is a flowchart of a specific implementation of the present invention for obtaining real-time compliance pressure and real-time lung volume. Step S2, obtaining real-time compliance pressure, specifically includes:

[0095] In step S21, the compensation resistance is obtained based on the airway pressure value and the real-time airway flow rate;

[0096] Specifically, in this embodiment, the calculation method for the compensating resistance is not limited. It can be based on fitting the respiratory mechanics equation during the inspiratory phase and using the least squares method to obtain the coefficient R, where R is the inspiratory resistance, and the product of the inspiratory resistance R and the real-time airway flow rate is used as the compensating resistance. Alternatively, the coefficient k can be calculated using the orifice model based on Bernoulli's principle, and the product of the coefficient k and the square of the real-time airway flow rate is used as the compensating resistance.

[0097] Specifically, in this embodiment, in order to reduce the amount of computation, it is preferable to obtain the inspiratory resistance R by fitting the respiratory mechanics equation during the inspiratory phase, and use the product of the inspiratory resistance R and the real-time airway flow rate as the compensating resistance.

[0098] In step S22, the real-time compliance pressure is calculated based on the compensation resistance.

[0099] Specifically, in this embodiment, the real-time compliance pressure is obtained by subtracting the compensation resistance from the airway pressure value using the following specific calculation formula:

[0100] P C =P aw -R·Flow

[0101] Among them, P C For real-time compliant pressure, P aw R is the airway pressure value, R is the inspiratory resistance, and Flow is the real-time flow rate.

[0102] By taking into account the influence of inhalation resistance, the method in this embodiment can obtain more accurate real-time compliance pressure while reducing the amount of computation.

[0103] Example 6

[0104] Please see Figure 5 , Figure 5 This is a schematic diagram of the lung overinflation coefficient measuring device provided by the present invention, as a reference. Figure 1 The implementation of the lung overinflation coefficient calculation method shown in this embodiment includes a lung overinflation coefficient calculation device. This device embodiment is similar to... Figure 1 Corresponding to the method embodiment shown, the apparatus includes:

[0105] Acquisition unit 21 is used to collect the patient's airway pressure value and real-time airway flow rate;

[0106] The first calculation unit 22 is used to obtain the real-time compliance pressure and the real-time lung volume based on the airway pressure value and the real-time airway flow rate.

[0107] The second calculation unit 23 is used to perform function fitting on real-time adaptive pressure and real-time volume to generate a first fitting function and a second fitting function.

[0108] The third calculation unit 24 is used to calculate and output the lung overinflation coefficient value based on the first fitting function and the second fitting function, as well as the effective inhalation time within any respiratory cycle.

[0109] The beneficial effect of the lung overinflation coefficient measuring device 20 in this embodiment of the invention is that by storing the parameter set of the fitting function, it is no longer necessary to store all the real-time data collected by the sensor. It can effectively represent the real-time compliance pressure and real-time volume, thereby calculating and outputting the patient's lung overinflation coefficient index, thereby reducing the data storage burden and effectively preventing the problem of insufficient memory or system task timeout, which would prevent the calculation of the lung overinflation coefficient.

[0110] Example 7

[0111] Please see Figure 6 This invention also provides a ventilator 10, which includes:

[0112] Sensor 11 is used to collect the patient's airway pressure and real-time airway flow rate;

[0113] One or more processors 12, working individually or collectively, are used to perform the following steps:

[0114] Based on the airway pressure value and the real-time airway flow rate, obtain the real-time compliance pressure and the real-time lung volume;

[0115] The real-time compliant pressure and the real-time volume are fitted by a function to generate a first fitting function and a second fitting function;

[0116] Based on the first fitting function and the second fitting function, and the effective inspiratory time within any respiratory cycle, calculate and output the lung overinflation coefficient value.

[0117] as well as

[0118] Memory 13 is used to store data.

[0119] Specifically, in this embodiment, sensor 11 includes at least a flow rate sensor and a proximal pressure sensor. Processor 12, in some embodiments, may be a central processing unit (CPU), controller, microcontroller, microprocessor, or other data processing chip. This processor 12 is typically used to control the overall operation of the ventilator.

[0120] In this embodiment, the processor 12 is used to run computer-readable instructions or process data stored in the memory 13, such as computer-readable instructions for running a method for calculating the lung overinflation coefficient of a ventilator in a non-constant flow state.

[0121] Those skilled in the art will understand that the memory 13 includes at least one type of readable storage medium, including flash memory, hard disk, multimedia card, card-type memory (e.g., SD or DX memory), random access memory (RAM), static random access memory (SRAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), programmable read-only memory (PROM), magnetic memory, disk, optical disk, etc.

[0122] In some embodiments, memory 13 may be an internal storage unit of the ventilator, such as the hard disk or memory of the ventilator.

[0123] In other embodiments, the memory 13 may also be an external storage device of the ventilator, such as a plug-in hard drive, smart media card (SMC), secure digital (SD) card, flash card, etc.

[0124] Of course, the memory 13 may include both the internal storage unit of the ventilator and its external storage device.

[0125] The beneficial effect of the ventilator 10 in this embodiment of the invention is that by storing the parameter set of the fitting function in the memory, it is no longer necessary to store all the real-time data collected by the sensor. This can effectively represent the real-time compliance pressure and real-time volume, thereby calculating and outputting the patient's lung overinflation coefficient index, thereby reducing the data storage burden and effectively preventing the problem of insufficient memory or system task timeout, which would prevent the calculation of the lung overinflation coefficient.

[0126] Example 8

[0127] This invention also provides a storage medium storing program instructions for executing the above-described method for calculating the lung overinflation coefficient under non-constant flow conditions.

[0128] The beneficial effect of the storage medium of the present invention is that by storing the parameter set of the fitting function in the memory, it is no longer necessary to store all the real-time data collected by the sensor. It can effectively represent the real-time compliance pressure and real-time volume, thereby calculating and outputting the patient's lung overinflation coefficient index, thereby reducing the data storage burden and effectively preventing the problem of insufficient memory or system task timeout, which would prevent the calculation of the lung overinflation coefficient.

[0129] This invention can be used in a wide range of general-purpose or special-purpose computer system environments or configurations.

[0130] Examples include: personal computers, server computers, handheld or portable devices, tablet devices, multiprocessor systems, microprocessor-based systems, set-top boxes, programmable consumer electronics, network PCs, minicomputers, mainframe computers, and distributed computing environments that include any of the above systems or devices.

[0131] The method of this invention generates a first and a second fitting function through function fitting, and saves the values ​​of the parameter set required for function fitting. This method effectively calculates the lung overinflation coefficient by storing the parameter set values, replacing the existing technology that requires storing all real-time data collected by sensors to calculate the lung overinflation coefficient. This reduces the data storage burden and effectively avoids the problem of insufficient memory or system timeouts due to large data storage requirements, thus preventing the calculation of the lung overinflation coefficient. Furthermore, through the specific implementation methods of embodiments one to eight, the computational load is reduced, the fitting time is shortened, the accuracy of function fitting is improved, and more accurate measurement values ​​are obtained.

[0132] It is understood that those skilled in the art can combine various implementation methods in the above embodiments under the guidance of the above examples to obtain technical solutions with multiple implementation methods.

[0133] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for calculating the lung overinflation coefficient, characterized in that, include: Collect the patient's airway pressure and real-time airway flow rate; Based on the airway pressure value and the real-time airway flow rate, obtain the real-time compliance pressure and the real-time lung volume; The real-time compliant pressure and the real-time volume are respectively fitted by functions to generate a first fitting function and a second fitting function; Based on the first fitting function and the second fitting function, and the effective inspiratory time within any respiratory cycle, calculate and output the lung overinflation coefficient value; The step of performing function fitting on the real-time compliance pressure and the real-time volume respectively is as follows: The starting point for initializing the function fitting is set, and the flow rate threshold is set. The real-time flow rate of the airway is compared with the flow rate threshold to determine whether the inhalation phase has ended. If the real-time flow rate of the airway is greater than the flow rate threshold, then the function fitting continues; If the real-time flow rate of the airway is less than or equal to the flow rate threshold, then stop function fitting; The initialization process includes setting the starting point volume of the function fitting to zero, and setting the pressure value of the starting point to the pressure value P0 monitored by the lower-level computer. The pressure value P0 is the end-expiratory pressure set by the doctor based on the patient's actual condition. The starting point for the function fitting is set to a first value. When the airway pressure value rises to the first value, the function fitting begins, wherein the first value is a set airway pressure threshold.

2. The method for calculating the lung overinflation coefficient as described in claim 1, characterized in that, When performing function fitting on the real-time compliant pressure and the real-time volume, the values ​​of the parameter set required for function fitting are calculated using the least squares method.

3. The method for calculating the lung overinflation coefficient as described in claim 1, characterized in that, When performing function fitting on the real-time compliant pressure and the real-time volume, a quadratic or cubic function is used for fitting.

4. The method for calculating the lung overinflation coefficient as described in claim 1, characterized in that, The step of obtaining real-time compliance pressure is as follows: The compensation resistance is obtained based on the airway pressure value and the real-time airway flow rate; The real-time compliance pressure is calculated based on the compensation resistance.

5. A device for calculating the lung overinflation coefficient, characterized in that, include: The acquisition unit is used to collect the patient's airway pressure and real-time airway flow rate; The first calculation unit is used to obtain the real-time compliance pressure and the real-time lung volume based on the airway pressure value and the real-time airway flow rate. The second calculation unit is used to perform function fitting on the real-time compliance pressure and the real-time volume respectively, and generate a first fitting function and a second fitting function. The third calculation unit is used to calculate and output the lung overexpansion coefficient value based on the first fitting function and the second fitting function, as well as the effective inhalation time within any respiratory cycle. The second computing unit is specifically used for: The starting point for initializing the function fitting is set, and the flow rate threshold is set. The real-time flow rate of the airway is compared with the flow rate threshold to determine whether the inhalation phase has ended. If the real-time flow rate of the airway is greater than the flow rate threshold, then the function fitting continues; If the real-time flow rate of the airway is less than or equal to the flow rate threshold, then stop function fitting; The initialization process includes setting the starting point volume of the function fitting to zero, and setting the pressure value of the starting point to the pressure value P0 monitored by the lower-level computer. The pressure value P0 is the end-expiratory pressure set by the doctor based on the patient's actual condition. The starting point for the function fitting is set to a first value. When the airway pressure value rises to the first value, the function fitting begins, wherein the first value is a set airway pressure threshold.

6. A ventilator, characterized in that, include: Sensors are used to collect patients' airway pressure and real-time airway flow rate; One or more processors, working individually or collectively, are used to perform the steps of the lung overinflation coefficient calculation method according to any one of claims 1 to 4; as well as A memory used to store data.

7. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores program instructions that, when executed by a processor, implement the steps of the lung overinflation coefficient calculation method according to any one of claims 1 to 4.

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