Breathing machine inspiration time compensation method and device, intelligent equipment and storage medium

Abstract

The invention is suitable for the technical field of breathing machines, and provides a breathing machine inspiration time compensation method and device, intelligent equipment and a storage medium. The method comprises the steps that the original inspiration time and the original inspiration flow peak value of the current breathing cycle of a patient are obtained; a sine flow change model is constructed according to the original inspiration time, the original inspiration flow peak value and a preset inspiration trigger flow threshold value, and compensation time is calculated based on the sine flow change model; and updating the original inspiration time according to the compensation time to obtain actual inspiration time. The method can improve the statistical precision of the inspiration time, improves the adaptability and reliability of the breathing machine to a dynamic breathing scene, assists a doctor in optimizing a ventilation strategy, and improves the treatment effect.

Description

Technical Field

[0001] The present application relates to the technical field of ventilators, and in particular to a method, apparatus, intelligent device and storage medium for compensating inspiratory time of a ventilator. Background Art

[0002] As an important medical assistive device, ventilators are widely used in both home treatment and clinical care for patients with chronic respiratory diseases. Their core function is to replace or assist the patient's spontaneous breathing through mechanical ventilation, providing personalized respiratory support for patients with chronic obstructive pulmonary disease (COPD), asthma, emphysema, and other conditions. Modern home ventilators acquire the patient's respiratory signals through flow sensors, and the core goal of their control algorithms is to achieve dynamic matching of inhalation triggering, air delivery maintenance, and expiratory switching.

[0003] Currently, mainstream home ventilators generally use a fixed flow threshold method to calculate inspiratory time. When the actual flow rate is detected to exceed the fixed flow threshold, the air supply program is started and the inspiratory phase begins. The inspiratory phase refers to the stage in the respiratory cycle when the patient actively or passively inhales gas. However, the inspiratory flow characteristics of different patients vary significantly, and the inspiratory flow waveform of the same patient changes dynamically under different physiological conditions. The fixed flow threshold method cannot adapt to individual differences and is difficult to track and adjust in real time. It is easy to cause a certain amount of inspiratory time to be lost, resulting in timing deviation. This deviation will reduce the doctor's accuracy in judging the patient's actual respiratory status, thereby affecting the accuracy of treatment decisions.

[0004] In view of this, how to improve the statistical accuracy of inspiratory time and realize personalized respiratory support for users by ventilators, thereby assisting doctors in optimizing ventilation strategies and improving treatment effects, is an issue that needs to be urgently addressed. Summary of the Invention

[0005] The embodiments of the present application provide a ventilator inspiratory time compensation method, apparatus, intelligent device and storage medium, which can improve the statistical accuracy of inspiratory time, improve the adaptability and reliability of the ventilator to dynamic respiratory scenarios, thereby assisting doctors in optimizing ventilation strategies and improving treatment effects.

[0006] In a first aspect, an embodiment of the present application provides a method for compensating inspiratory time of a ventilator, comprising:

[0007] Obtain the original inspiratory time and original inspiratory flow peak of the patient's current respiratory cycle;

[0008] Constructing a sinusoidal flow variation model according to the original inspiratory time, the original inspiratory flow peak value, and a preset inspiratory trigger flow threshold, and calculating a compensation time based on the sinusoidal flow variation model;

[0009] The original inspiratory time is updated according to the compensation time to obtain the actual inspiratory time.

[0010] In a possible implementation of the first aspect, the expression of the sine flow rate change model Q(T c ) includes:

[0011]

[0012] Calculate the compensation time T according to the following calculation formula c :

[0013]

[0014] where T i represents the original inspiration time, L represents the inspiration trigger flow rate threshold, and a represents the original inspiration flow rate peak.

[0015] In a possible implementation of the first aspect, the step of obtaining the original inspiration time and the original inspiration flow rate peak of the patient's current respiratory cycle includes:

[0016] Read the preset inspiration trigger flow rate threshold;

[0017] Collect the patient's respiratory flow rate in real time through a flow sensor;

[0018] Based on the collected respiratory flow rate and the inspiration trigger flow rate threshold, determine the start time of inspiration trigger;

[0019] According to the start time of inspiration trigger and the respiratory flow rate, determine the original inspiration time and the original inspiration flow rate peak of the patient's current respiratory cycle.

[0020] In a possible implementation of the first aspect, the step of reading the preset inspiration trigger flow rate threshold includes:

[0021] Determine the current working gear of the ventilator;

[0022] Read the preset inspiration trigger flow rate threshold at the current working gear.

[0023] In a possible implementation of the first aspect, after the step of updating the original inspiration time according to the compensation time to obtain the actual inspiration time, it further includes:

[0024] Calculate the error rate according to the actual inspiration time and the original inspiration time;

[0025] If the error rate is greater than the preset error rate threshold, trigger the reset of the model parameters of the sine flow rate change model.

[0026] In a possible implementation of the first aspect, the reset of the model parameters includes:

[0027] Obtain the inspiratory time and peak inspiratory flow rate within a continuous preset number of respiratory cycles of the patient;

[0028] Determine the inspiratory calibration time and the peak inspiratory flow rate for calibration, where the inspiratory calibration time is the average value of the inspiratory times within the continuous preset number of respiratory cycles, and the peak inspiratory flow rate for calibration is the average value of the peak inspiratory flow rates;

[0029] Reset the model parameters of the sine flow rate change model according to the inspiratory calibration time and the peak inspiratory flow rate for calibration.

[0030] In a possible implementation manner of the first aspect, the method further includes:

[0031] When the ratio of the inspiratory trigger flow rate threshold to the original peak inspiratory flow rate is greater than 1, adjust the preset inspiratory trigger flow rate threshold according to a preset adjustment strategy.

[0032] In a second aspect, an embodiment of the present application provides a device for compensating the inspiratory time of a ventilator, including:

[0033] A data acquisition unit, configured to acquire the original inspiratory time and the original peak inspiratory flow rate of the patient's current respiratory cycle;

[0034] A compensation calculation unit, configured to construct a sine flow rate change model according to the original inspiratory time, the original peak inspiratory flow rate, and a preset inspiratory trigger flow rate threshold, and calculate a compensation time based on the sine flow rate change model;

[0035] A time update unit, configured to update the original inspiratory time according to the compensation time to obtain the actual inspiratory time.

[0036] In a third aspect, an embodiment of the present application provides an intelligent device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the method for compensating the inspiratory time of a ventilator as described in the first aspect above is implemented.

[0037] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium storing a computer program, and when the computer program is executed by a processor, the method for compensating the inspiratory time of a ventilator as described in the first aspect above is implemented.

[0038] In a fifth aspect, an embodiment of the present application provides a computer program product, which when running on an intelligent device, causes the intelligent device to execute the method for compensating the inspiratory time of a ventilator as described in the first aspect above.

[0039] In the embodiments of the present application, the original inhalation time and the peak inhalation flow rate that can reflect the characteristics of the patient's current breathing pattern within the current breathing cycle of the patient are obtained, and a sine flow rate change model is constructed based on the original inhalation time, the peak inhalation flow rate, and a preset inhalation trigger flow rate threshold. The compensation time is calculated based on the sine flow rate change model, and the original inhalation time is updated using the compensation time, thereby achieving accurate compensation and optimization of the original inhalation time. The present application can effectively improve the accuracy of inhalation time statistics. Through accurate calculation of the compensation time, the ventilator can provide personalized breathing support for the user, and at the same time, it can also provide more accurate breathing support data for doctors, assisting doctors in optimizing the ventilation strategy, reducing unnecessary ventilation fluctuations and errors, and thus improving the treatment effect. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the following will briefly introduce the drawings required for use in the embodiments or the description of the prior art. Obviously, the following drawings are only some embodiments of the present application. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained based on these drawings.

[0041] Figure 1 is the implementation flowchart of the method for compensating the inhalation time of the ventilator provided by the embodiments of the present application;

[0042] Figure 2 is a specific implementation flowchart of step S102 in the method for compensating the inhalation time of the ventilator provided by the embodiments of the present application;

[0043] Figure 3 is a specific implementation flowchart of reading the flow rate threshold in the method for compensating the inhalation time of the ventilator provided by the embodiments of the present application;

[0044] Figure 4 is a schematic diagram showing the compensation time in the method for compensating the inhalation time of the ventilator provided by the embodiments of the present application;

[0045] Figure 5 is a specific implementation flowchart of triggering the reset of the model parameters in the method for compensating the inhalation time of the ventilator provided by the embodiments of the present application;

[0046] Figure 6 is a specific implementation flowchart of resetting the model parameters in the method for compensating the inhalation time of the ventilator provided by the embodiments of the present application;

[0047] Figure 7 is the structural block diagram of the device for compensating the inhalation time of the ventilator provided by the embodiments of the present application;

[0048] Figure 8 is a schematic diagram of the intelligent device provided by the embodiments of the present application. Detailed implementation manners

[0049] In the following description, for the purpose of illustration rather than limitation, specific details such as specific system architectures, technologies, etc. are provided to thoroughly understand the embodiments of the present application. However, those skilled in the art should clearly understand that the present application can also be implemented in other embodiments without these specific details. In other cases, detailed descriptions of well-known systems, devices, circuits, and methods are omitted to avoid unnecessary details from interfering with the description of the present application.

[0050] It should be understood that when used in the specification of the present application and the appended claims, the term "comprising" indicates the presence of the described features, wholes, steps, operations, elements, and / or components, but does not exclude the presence or addition of one or more other features, wholes, steps, operations, elements, components, and / or their combinations.

[0051] It should also be understood that the term "and / or" used in the specification of the present application and the appended claims refers to any combination and all possible combinations of one or more of the associated listed items, and includes these combinations.

[0052] As used in the specification of the present application and the appended claims, the term "if" can be interpreted as "when", "once", "in response to determining", or "in response to detecting" according to the context. Similarly, the phrase "if determined" or "if [the described condition or event] is detected" can be interpreted as meaning "once determined", "in response to determining", "once [the described condition or event] is detected", or "in response to detecting [the described condition or event]" according to the context.

[0053] In addition, in the description of the specification of the present application and the appended claims, the terms "first", "second", "third", etc. are only used for distinguishing descriptions and cannot be understood as indicating or implying relative importance.

[0054] The reference to "one embodiment" or "some embodiments" etc. described in the specification of the present application means that a specific feature, structure, or characteristic described in connection with the embodiment is included in one or more embodiments of the present application. Thus, the statements "in one embodiment", "in some embodiments", "in other some embodiments", "in still other embodiments", etc. that appear in different places in this specification do not necessarily all refer to the same embodiment, but mean "one or more but not all embodiments", unless otherwise specifically emphasized in other ways. The terms "comprising", "including", "having", and their variants all mean "including but not limited to", unless otherwise specifically emphasized in other ways.

[0055] In the prior art, based on the fact that the inspiration trigger threshold is generally a set threshold, such as 2 L / min, and the calculation of the inspiration time only starts after the inspiration trigger is detected. However, the breathing flow rate at the actual start of the patient's inspiration may be lower than the set threshold, resulting in the ventilator misjudging the starting point of inspiration and causing a certain loss of inspiration time. The timing deviation caused by this loss will reduce the doctor's judgment accuracy of the patient's actual breathing state.

[0056] To compensate for this loss, the present application proposes a method for compensating the inspiration time of a ventilator. By obtaining the original inspiration time and the peak inspiration flow rate within the current breathing cycle of the patient, and constructing a sine flow rate change model based on the original inspiration time, the peak inspiration flow rate, and a preset inspiration trigger flow rate threshold, the compensation time is calculated based on this sine flow rate change model, and the original inspiration time is updated using the compensation time, thereby achieving precise compensation and optimization of the original inspiration time.

[0057] By way of example and not limitation, the method for compensating the inspiration time of a ventilator provided in the embodiments of the present application can be applied to various types of intelligent devices, specifically including intelligent devices such as ventilators, mobile phones, tablet computers, laptop computers, ultra-mobile personal computers (UMPCs), desktop computers, etc. that can issue control commands. The embodiments of the present application do not impose any restrictions on the specific types of intelligent devices.

[0058] Figure 1 The implementation process of the method for compensating the inspiration time of a ventilator provided in the embodiments of the present application is shown. This method process includes steps S101 to S103. The specific implementation principles of each step are as follows:

[0059] Step S101: Obtain the original inspiration time and the peak original inspiration flow rate of the patient's current breathing cycle.

[0060] The breathing cycle refers to the time period from the start of inspiration to the end of expiration. A breathing cycle includes a complete inspiration phase and an expiration phase. The original inspiration time is the detected duration of the inspiration phase. The peak original inspiration flow rate is the maximum value of the breathing flow rate within the inspiration phase, which can reflect the patient's effort during inspiration. The original inspiration time and the peak original inspiration flow rate are the basic data for subsequent calculation of the compensation time.

[0061] As a possible implementation manner of the present application, Figure 2 A specific implementation process of step S101 in the method for compensating the inspiration time of a ventilator provided in the embodiments of the present application is shown and is described in detail as follows:

[0062] A1: Read the preset inspiration trigger flow rate threshold.

[0063] The inspiratory trigger flow threshold and the expiratory trigger flow threshold are preset parameters, which can be adjusted according to the patient's condition and patient type. For example, for general patients, the inspiratory trigger flow threshold is set to 2 L / min and the expiratory trigger flow threshold is set to -2 L / min; for children, the inspiratory trigger flow threshold is set to 1 L / min and the expiratory trigger flow threshold is set to -1 L / min. The inspiratory trigger flow threshold and the expiratory trigger flow threshold are symmetric.

[0064] In a possible implementation, as Figure 3 shown, the step of reading the preset inspiratory trigger flow threshold includes:

[0065] A11: Determine the current working mode of the ventilator. The working mode refers to the preset ventilation support strength level of the ventilator. The higher the level, the stronger the support of the ventilator. The current working mode of the ventilator can be determined according to the selected mode on the ventilator panel knob or touch screen.

[0066] The ventilator has multiple preset working modes, which are used to distinguish the severity of the patient's condition or meet the treatment needs. The higher the mode, the stronger the auxiliary strength of the ventilator. For example, it is divided into 1-3 modes (such as mode 1: mild respiratory disorder, low support + high trigger threshold to reduce interference; mode 3: severe chronic obstructive pulmonary disease, high support + low trigger threshold to reduce respiratory power consumption). The working mode is personalized associated with the patient's state. For example, mode 1 is applicable to patient A in the recovery period, and mode 3 is applicable to patient B with chronic obstructive pulmonary disease.

[0067] In a possible implementation, the mode is negatively correlated with the sensitivity of the trigger flow threshold. The higher the mode (the stronger the support), the lower the inspiratory trigger flow threshold (the higher the sensitivity), and the smaller the absolute value of the expiratory trigger threshold. On the contrary, the lower the mode (the weaker the support), the higher the inspiratory trigger flow threshold (the lower the sensitivity), and the larger the absolute value of the expiratory trigger threshold.

[0068] A12: Read the preset inspiratory trigger flow threshold in the working mode.

[0069] The trigger flow threshold corresponding to each working mode of the ventilator is different. The inspiratory trigger flow threshold and the expiratory trigger flow threshold corresponding to the current working mode can be found by reading the mode threshold comparison table.

[0070] In this embodiment, by determining the inspiratory trigger flow threshold and the expiratory trigger flow threshold matched with the working mode of the ventilator, the current inspiratory trigger flow threshold of the ventilator can be accurately read, which lays a foundation for the accuracy of subsequent inspiratory time calculation.

[0071] A2: Real-time collect the patient's respiratory flow through a flow sensor.

[0072] The flow sensor collects the patient's respiratory flow in real time. The currently collected respiratory flow may be inhalation flow data or exhalation flow data. The high-precision flow sensor captures the changes in the patient's respiratory flow in real time, providing the original data support for subsequent trigger time determination, sine model fitting, and compensation time calculation. The type and model of the flow sensor are not limited in this embodiment.

[0073] A3: Based on the collected respiratory flow and the inhalation trigger flow threshold, determine the start time of inhalation trigger.

[0074] When the respiratory flow is higher than the inhalation trigger flow threshold for the first time, inhalation is triggered, and the current time is determined as the start time of inhalation trigger, marking the beginning of the theoretical inhalation phase.

[0075] Based on the collected exhalation flow data and the exhalation trigger flow threshold, determine the start time of exhalation trigger.

[0076] When the respiratory flow is lower than the exhalation trigger flow threshold, exhalation is triggered, and the current time is determined as the start time of exhalation.

[0077] Exemplarily, the inhalation trigger flow threshold is set to 2 L / min, and the exhalation trigger flow threshold is set to -2 L / min. When the respiratory flow is higher than 2 L / min, the ventilator recognizes that the patient is inhaling; when the respiratory flow is lower than -2 L / min, the ventilator recognizes that the patient is exhaling.

[0078] Through the recognition of two inhalation triggers, the intelligent device can accurately identify a complete exhalation cycle, ensuring the accurate correspondence between inhalation and exhalation timing.

[0079] In a possible implementation, to avoid false triggering, inhalation trigger is determined only when the respiratory flow is higher than the inhalation trigger flow threshold for the first time and lasts for a preset duration. Similarly, exhalation trigger is determined only when the respiratory flow is lower than the exhalation trigger flow threshold for the first time and lasts for a preset duration. This preset duration can be set according to the actual application scenario of the ventilator and the sensitivity of the ventilator. For example, the preset duration is 50 ms, and the time when the patient's respiratory flow exceeds the inhalation trigger flow threshold for the first time and lasts for 50 ms is determined as the start time of inhalation trigger.

[0080] A4: According to the start time of inhalation trigger and the respiratory flow, determine the original inhalation time and the original peak inhalation flow of the patient's current respiratory cycle.

[0081] Fit the respiratory flow collected by the flow sensor into a respiratory flow waveform. Based on this respiratory flow waveform, determine the time period from the start time of inhalation trigger to the end time of the inhalation phase as the original inhalation time. At the same time, determine the maximum value of the respiratory flow during the inhalation phase and determine this maximum value as the original peak inhalation flow.

[0082] In the embodiment of the present application, the original inspiration time and the original peak inspiration flow rate are obtained in each respiratory cycle of the patient, that is, the original inspiration time and the original peak inspiration flow rate are updated in real time to adapt to the changes in the patient's respiratory characteristics. Through the real-time acquisition of the respiratory flow rate and the threshold reading, the starting moment of inspiration trigger is dynamically determined to ensure the accuracy of the original inspiration time and the peak flow rate, providing a highly reliable input for the respiratory compensation algorithm.

[0083] Step S102: Construct a sine flow rate change model according to the original inspiration time, the original peak inspiration flow rate, and a preset inspiration trigger flow rate threshold, and calculate the compensation time based on the sine flow rate change model.

[0084] During the respiratory cycle, the flow rate change in the inspiration phase conforms to the sine wave law. Based on this, a sine flow rate change model is constructed to simulate the patient's breathing pattern and reflect the change in the inspiration flow rate during the inspiration phase.

[0085] As a possible implementation manner of the present application, in order to compensate for the loss caused by the set inspiration trigger flow rate threshold, the respiratory flow rate corresponding to the loss time of the inspiration flow rate sine wave is set as the inspiration trigger flow rate threshold. Based on this, the constructed sine flow rate change model Q(T c ) has the following expression:

[0086]

[0087] The compensation time T is calculated according to the following calculation formula (2) c :

[0088]

[0089] Among them, Q(T c ) represents the sine flow rate change model, T i represents the original inspiration time, L represents the inspiration trigger flow rate threshold, and a represents the original peak inspiration flow rate. T i represents the original inspiration time, L represents the inspiration trigger flow rate threshold, and a represents the original peak inspiration flow rate. T represents the total sine cycle time, and the total sine cycle time is equivalent to the time of one respiratory cycle of the patient.

[0090] In the embodiment of the present application, by constructing a sine flow rate change model, the respiratory characteristics of the patient, such as the original inspiration time and the original peak inspiration flow rate, are converted into quantifiable parameters, which helps to accurately calculate the compensation time, thereby significantly improving the statistical accuracy of the inspiration time and providing core technical support for the personalized support of the ventilator and the optimization of medical decisions.

[0091] Step S103: Update the original inspiration time according to the compensation time to obtain the actual inspiration time.

[0092] In the embodiment of the present application, as Figure 4 shown, in the inhalation phase, the time from detecting the inhalation trigger to the end of the inhalation phase is the original inhalation time T i , and the actual inhalation time T r is the sum of the compensation time T c and the original inhalation time T i , that is, the actual inhalation time T r = T i + T c .

[0093] The fixed threshold method causes statistical deviation of the original inhalation time. In the embodiment of the present application, the compensation time is calculated by fitting with a sine flow rate change model, and the original inhalation time is updated using the compensation time, realizing precise compensation and optimization of the original inhalation time, and effectively improving the accuracy of inhalation time statistics.

[0094] As a possible implementation manner of the present application, Figure 5 shows a specific implementation process of resetting the model parameters of the sine flow rate change model according to the error rate in the inhalation time compensation method of the ventilator provided by the embodiment of the present application, which is described in detail as follows:

[0095] B1: Calculate the error rate according to the actual inhalation time and the original inhalation time.

[0096] The error rate is the deviation ratio of the actual inhalation time to the original inhalation time. The calculation of the error rate is as follows formula (3):

[0097]

[0098] where η represents the error rate, T r represents the actual inhalation time, and T i represents the original inhalation time.

[0099] B2: If the error rate is greater than the preset error rate threshold, trigger the reset of the model parameters of the sine flow rate change model. The preset error rate threshold is the maximum allowable error rate. If the error rate of the current breathing cycle exceeds the preset error rate threshold, it is considered that the model parameters are mismatched. The reset of the model parameters includes re-initializing model parameters such as the original inhalation time and the peak value of the original inhalation flow rate. Set the critical condition for triggering model reset to avoid overcorrection or error accumulation.

[0100] As the patient's breathing pattern changes (such as from deep and slow breathing to shallow and rapid breathing), the original model parameters cannot adapt to the new waveform, resulting in a continuous increase in the error rate. In the embodiments of the present application, by calculating the correction amplitude of the error rate quantization compensation algorithm, it is determined whether the sine flow change model needs to be reset. Through error rate monitoring and parameter reset, the model is forced to relearn the current breathing characteristics to avoid long-term deviation.

[0101] In a possible implementation manner, as Figure 6 shown, the reset of the model parameters includes:

[0102] B21: Obtain the inhalation time and the peak inhalation flow rate within a continuous preset number of breathing cycles of the patient. By collecting multi-cycle data, the interference of single-breath abnormalities (such as coughing and swallowing actions) on parameter calibration is reduced. For example, if the peak inhalation flow rate suddenly drops due to coughing during a certain breath, the influence of abnormal values can be diluted through multi-cycle averaging. At the same time, the gradual changes in the patient's breathing pattern are captured to provide a trend basis for dynamic calibration.

[0103] B22: Determine the inhalation calibration time and the peak inhalation flow rate for calibration. The inhalation calibration time is the average value of the inhalation times within the continuous preset number of breathing cycles, and the peak inhalation flow rate for calibration is the average value of the peak inhalation flow rates. Through mean calculation, the parameter fluctuations caused by accidental factors (such as body position changes and temporary shortness of breath) are suppressed, thereby improving the stability of the calibrated parameters.

[0104] B23: Reset the model parameters of the sine flow change model according to the inhalation calibration time and the peak inhalation flow rate for calibration.

[0105] By resetting the model parameters, new breathing characteristics can be quickly matched to avoid error accumulation caused by parameter lag.

[0106] In a possible implementation manner, within the current exhalation cycle, when the ratio of the inhalation trigger flow threshold to the original peak inhalation flow rate is greater than 1, according to a preset adjustment strategy, the preset inhalation trigger flow threshold is adjusted. For example, first, the preset adjustment strategy includes adjusting the inhalation trigger flow threshold to a preset proportion of the original peak inhalation flow rate. For example, the inhalation trigger flow threshold is adjusted to 80% of the original peak inhalation flow rate. Second, the preset adjustment strategy includes adjusting the inhalation trigger flow threshold based on the historical average peak flow rate. The preset adjustment strategy can be determined according to the application scenario of the ventilator, the patient's needs or choices, etc. The preset adjustment strategy can be any one of these two. The adjusted inhalation trigger flow threshold is used for the identification of inhalation trigger in the next breathing cycle.

[0107] The embodiments of the present application monitor the ratio of the inspiratory trigger flow threshold to the original inspiratory flow peak value, actively correct abnormal threshold settings, and avoid misjudgment caused by sensor noise or short-term respiratory fluctuations. Moreover, by automatically adjusting the inspiratory trigger flow threshold, it is possible to avoid the inability to trigger the inspiratory phase due to too high a threshold, thereby ensuring that the ventilator continuously provides effective support for the patient.

[0108] As can be seen from the above, in the embodiments of the present application, the original inspiratory time and the inspiratory flow peak value that can reflect the current respiratory mode characteristics of the patient in the current respiratory cycle are obtained, and a sine flow change model is constructed based on the original inspiratory time, the inspiratory flow peak value, and the preset inspiratory trigger flow threshold. The compensation time is calculated based on the sine flow change model, and the original inspiratory time is updated using the compensation time, thereby achieving precise compensation and optimization of the original inspiratory time. The present application can effectively improve the accuracy of inspiratory time statistics. Through accurate compensation time calculation, it realizes personalized respiratory support of the ventilator for users, and at the same time provides more accurate respiratory support data for doctors, assisting doctors in optimizing ventilation strategies, reducing unnecessary ventilation fluctuations and errors, and thus improving the treatment effect.

[0109] It should be understood that the magnitudes of the sequence numbers of the steps in the above embodiments do not mean the order of execution. The order of execution of each process should be determined by its function and internal logic, and should not constitute any limitation to the implementation process of the embodiments of the present application.

[0110] Corresponding to the ventilator inspiratory time compensation method described in the above embodiments, Figure 7 The structural block diagram of the ventilator inspiratory time compensation device provided by the embodiments of the present application is shown. For the sake of convenience of description, only the parts related to the embodiments of the present application are shown.

[0111] Refer to Figure 7 The ventilator inspiratory time compensation device includes: a data acquisition unit 71, a compensation calculation unit 72, and a time update unit 73, where:

[0112] The data acquisition unit 71 is configured to acquire the original inspiratory time and the original inspiratory flow peak value of the patient's current respiratory cycle;

[0113] The compensation calculation unit 72 is configured to construct a sine flow change model according to the original inspiratory time, the original inspiratory flow peak value, and a preset inspiratory trigger flow threshold, and calculate a compensation time based on the sine flow change model;

[0114] The time update unit 73 is configured to update the original inspiratory time according to the compensation time to obtain the actual inspiratory time.

[0115] As a possible implementation manner of the present application, the sine flow change model Q(T c) The expression includes:

[0116]

[0117] Calculate the compensation time T according to the following calculation formula c :

[0118]

[0119] Wherein, T i represents the original inspiration time, L represents the inspiration trigger flow threshold, and a represents the original inspiration flow peak.

[0120] As a possible implementation manner of the present application, the data acquisition unit 71 includes:

[0121] A preset threshold reading module, configured to read a preset inspiration trigger flow threshold;

[0122] A flow data acquisition module, configured to collect the breathing flow of the patient in real time through a flow sensor;

[0123] A breathing trigger determination module, configured to determine the starting moment of inspiration trigger based on the collected breathing flow and the inspiration trigger flow threshold;

[0124] A data determination module, configured to determine the original inspiration time and the original inspiration flow peak of the current breathing cycle of the patient according to the starting moment of inspiration trigger and the breathing flow.

[0125] As a possible implementation manner of the present application, the preset threshold reading module is specifically configured to:

[0126] Determine the current working gear of the ventilator;

[0127] Read the preset inspiration trigger flow threshold at the working gear.

[0128] As a possible implementation manner of the present application, the ventilator inspiration time compensation device further includes:

[0129] An error rate calculation unit, configured to calculate an error rate according to the actual inspiration time and the original inspiration time;

[0130] A parameter reset unit, configured to trigger reset of the model parameters of the sine flow change model if the error rate is greater than a preset error rate threshold.

[0131] As a possible implementation manner of the present application, the parameter reset unit includes:

[0132] A continuous cycle data acquisition module, configured to acquire the inspiration time and the inspiration flow peak within a continuous preset number of breathing cycles of the patient;

[0133] An average value acquisition module, configured to determine an inhalation calibration time and an inhalation flow calibration peak value, where the inhalation calibration time is an average value of the inhalation times within the continuous preset number of respiratory cycles, and the inhalation flow calibration peak value is an average value of the inhalation flow peak values;

[0134] A model parameter reset module, configured to reset the model parameters of the sine flow change model according to the inhalation calibration time and the inhalation flow calibration peak value.

[0135] As a possible implementation manner of the present application, the ventilator inhalation time compensation device further includes:

[0136] A threshold adjustment unit, configured to, when a ratio of the inhalation trigger flow threshold to the original inhalation flow peak value is greater than 1, adjust the preset inhalation trigger flow threshold according to a preset adjustment strategy.

[0137] As can be seen from the above, in the embodiments of the present application, by acquiring the original inhalation time and the inhalation flow peak value that can reflect the current breathing mode characteristics of the patient within the current respiratory cycle of the patient, and constructing a sine flow change model according to the original inhalation time, the inhalation flow peak value, and the preset inhalation trigger flow threshold, calculating a compensation time based on the sine flow change model, and updating the original inhalation time with the compensation time, the accurate compensation and optimization of the original inhalation time are realized. The present application can effectively improve the accuracy of inhalation time statistics, realize the personalized breathing support of the ventilator for the user through accurate compensation time calculation, and at the same time provide more accurate breathing support data for doctors, assist doctors in optimizing the ventilation strategy, reduce unnecessary ventilation fluctuations and errors, and thus improve the treatment effect.

[0138] It should be noted that for the information interaction, execution process, etc. between the above-mentioned device / unit, since it is based on the same concept as the method embodiment of the present application, the specific functions and the technical effects brought by them can be specifically referred to the method embodiment part, and will not be elaborated here.

[0139] The embodiments of the present application further provide a computer-readable storage medium, where the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, it implements the steps of any one of the Figures 1 to 6 ventilator inhalation time compensation methods shown.

[0140] The embodiments of the present application further provide an intelligent device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the steps of any one of the Figures 1 to 6 ventilator inhalation time compensation methods shown.

[0141] The embodiments of the present application further provide a computer program product. When the computer program product runs on an intelligent device, the intelligent device is enabled to execute the steps of implementing any one of the ventilator inspiratory time compensation methods as Figures 1 to 6 shown.

[0142] Figure 8 FIG. is a schematic diagram of an intelligent device provided by an embodiment of the present application. As Figure 8 shown, the intelligent device 8 in this embodiment includes: a processor 80, a memory 81, and a computer program 82 stored in the memory 81 and executable on the processor 80. When the processor 80 executes the computer program 82, the steps in the above-mentioned embodiments of various ventilator inspiratory time compensation methods are implemented, for example Figure 1 the steps S101 to S103 shown. Alternatively, when the processor 80 executes the computer program 82, the functions of each module / unit in the above-mentioned device embodiments are implemented, for example Figure 7 the functions of the units 71 to 73 shown.

[0143] Exemplarily, the computer program 82 may be divided into one or more modules / units. The one or more modules / units are stored in the memory 81 and executed by the processor 80 to complete the present application. The one or more modules / units may be a series of computer-readable instruction segments capable of performing specific functions, and the instruction segments are used to describe the execution process of the computer program 82 in the intelligent device 8.

[0144] The intelligent device 8 may include, but is not limited to, a processor 80 and a memory 81. Those skilled in the art can understand that Figure 8 this is only an example of the intelligent device 8 and does not constitute a limitation on the intelligent device 8. It may include more or fewer components than shown in the figure, or combine certain components, or different components. For example, the intelligent device 8 may further include input / output devices, network access devices, buses, etc.

[0145] The processor 80 may be a central processing unit (CPU), or may also be other general-purpose processors, digital signal processors (DSPs), application specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc.

[0146] The memory 91 may be an internal storage unit of the intelligent device 9, such as a hard disk or memory of the intelligent device 9. The memory 91 may also be an external storage device of the intelligent device 9, such as a plug-in hard disk equipped on the intelligent device 9, a Smart Media Card (SMC), a Secure Digital (SD) card, a Flash Card, etc. Further, the memory 91 may also include both the internal storage unit and the external storage device of the intelligent device 9. The memory 91 is used to store the computer program and other programs and data required by the intelligent device. The memory 91 may also be used to temporarily store the data that has been output or will be output.

[0147] It should be noted that, for the information interaction, execution process, etc. between the above-mentioned device / units, since they are based on the same concept as the method embodiment of the present application, for their specific functions and the technical effects brought, reference may be specifically made to the method embodiment part, and details are not described herein again.

[0148] Those skilled in the art can clearly understand that, for the convenience and simplicity of description, only the above division of each functional unit and module is used for illustration. In actual applications, the above functions can be allocated to different functional units and modules according to needs, that is, the internal structure of the device is divided into different functional units or modules to complete all or part of the functions described above. Each functional unit and module in the embodiment can be integrated in a processing unit, or each unit can exist physically alone, or two or more units can be integrated in one unit. The above integrated unit can be implemented in the form of hardware or in the form of a software functional unit. In addition, the specific names of each functional unit and module are only for the convenience of mutual distinction and do not limit the protection scope of the present application. The specific working process of the units and modules in the above system can refer to the corresponding process in the foregoing method embodiment, and details are not described herein again.

[0149] When the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, to implement all or part of the processes in the above-mentioned embodiment methods of this application, a computer program can be used to instruct the relevant hardware to complete. The computer program can be stored in a computer-readable storage medium. When the computer program is executed by a processor, the steps of the above-mentioned various method embodiments can be implemented. Among them, the computer program includes computer program code, and the computer program code can be in the form of source code, object code, executable file or some intermediate form, etc. The computer-readable medium can at least include: any entity or device capable of carrying the computer program code to the device / terminal device, recording medium, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signal, telecommunication signal, and software distribution medium. For example, a USB flash drive, a mobile hard disk, a magnetic disk, or an optical disc, etc. In some jurisdictions, according to legislation and patent practice, the computer-readable medium cannot be an electrical carrier signal and a telecommunication signal.

[0150] In the above embodiments, the descriptions of the various embodiments have their own emphases. For the parts not detailed or recorded in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0151] The above-mentioned embodiments are only used to illustrate the technical solutions of this application, rather than to limit them; although this application has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that: they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements on some of the technical features; and these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the various embodiments of this application, and should all be included in the protection scope of this application.

Claims

1. A method for compensating the inspiratory time of a ventilator, characterized in that, Including: Obtaining the original inspiration time and the original peak inspiration flow rate of the patient's current respiratory cycle; Constructing a sine flow rate change model based on the original inspiration time, the original peak inspiration flow rate, and a preset inspiration trigger flow rate threshold, and calculating a compensation time based on the sine flow rate change model; Updating the original inspiration time according to the compensation time to obtain the actual inspiration time.

2. The method according to claim 1, wherein The sine flow rate change model Q(T c ) has an expression that includes: Calculate the compensation time T according to the following calculation formula c :[[]]END]] Among them, T i represents the original inspiration time, L represents the inspiration trigger flow threshold, and a represents the original peak inspiration flow rate.

3. The method according to claim 1, wherein The step of obtaining the original inspiration time and the original peak inspiration flow rate of the patient's current respiratory cycle includes: Reading a preset inspiration trigger flow rate threshold; Collecting the patient's respiratory flow rate in real time through a flow sensor; Determining the inspiration trigger start time based on the collected respiratory flow rate and the inspiration trigger flow rate threshold; Determining the original inspiration time and the original peak inspiration flow rate of the patient's current respiratory cycle according to the inspiration trigger start time and the respiratory flow rate.

4. The method according to claim 3, wherein The step of reading a preset inspiration trigger flow rate threshold includes: Determining the current working gear of the ventilator; Reading the preset inspiration trigger flow rate threshold at the current working gear.

5. The method according to claim 1, characterized in that, After the step of updating the original inspiration time according to the compensation time to obtain the actual inspiration time, it further includes: Calculating an error rate based on the actual inspiration time and the original inspiration time; If the error rate is greater than a preset error rate threshold, triggering a reset of the model parameters of the sine flow rate change model.

6. The method according to claim 5, characterized in that, The model parameter reset includes: Obtaining the inspiration time and the peak inspiration flow rate within a preset number of consecutive respiratory cycles of the patient; Determining an inspiration calibration time and a peak inspiration flow rate calibration value, where the inspiration calibration time is the average value of the inspiration times within the preset number of consecutive respiratory cycles, and the peak inspiration flow rate calibration value is the average value of the peak inspiration flow rates; Resetting the model parameters of the sine flow rate change model according to the inspiration calibration time and the peak inspiration flow rate calibration value.

7. The method according to any one of claims 1 to 6, characterized in that The method further includes: When the ratio of the inspiration trigger flow rate threshold to the original peak inspiration flow rate is greater than 1, adjusting the preset inspiration trigger flow rate threshold according to a preset adjustment strategy.

8. A ventilator inspiratory time compensation device, characterized in that, Including: A data acquisition unit for obtaining the original inspiration time and the original peak inspiration flow rate of the patient's current respiratory cycle; A compensation calculation unit for constructing a sine flow rate change model based on the original inspiration time, the original peak inspiration flow rate, and a preset inspiration trigger flow rate threshold, and calculating a compensation time based on the sine flow rate change model; A time update unit for updating the original inspiration time according to the compensation time to obtain the actual inspiration time.

9. An intelligent device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the ventilator inspiration time compensation method according to any one of claims 1 to 7.

10. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by a processor, it implements the ventilator inspiration time compensation method according to any one of claims 1 to 7.

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