Lung function residual gas volume detection method for pneumonia recovery period patient

Abstract

The invention discloses a lung function residual gas volume detection method for a patient in a pneumonia recovery period, and belongs to the technical field of lung function residual gas volume detection for the patient in the pneumonia recovery period, and the method comprises the following steps: determining a basic detection mode, identifying basic information of the basic detection mode, carrying out condition evaluation according to the basic information, and obtaining a condition evaluation result, performing corresponding processing according to the condition evaluation result; performing airway obstruction assessment on the patient to obtain an airway assessment result; guiding the patient to prepare for breathing; performing lung function residual gas volume detection on the patient according to the basic detection mode to obtain an initial detection result, and correcting the initial detection result according to the airway evaluation result to obtain a target monitoring result; parameters such as washing-in and washing-out speed, flow and the like of the gas are accurately controlled and optimized, so that the gas can be kept in a relatively stable state in different detection environments, and interference of external factors on a detection result is reduced.

Description

Technical Field

[0001] This invention belongs to the field of residual lung volume detection technology for patients in the recovery period of pneumonia, specifically a method for detecting residual lung volume in patients in the recovery period of pneumonia. Background Technology

[0002] Pneumonia is a common respiratory disease. During the recovery period, patients' lung function often has not fully recovered, and varying degrees of ventilation dysfunction may exist. Functional Residual Capacity (FRC), as one of the important indicators reflecting lung ventilation function, is of great significance for assessing the lung function status of patients recovering from pneumonia, guiding rehabilitation treatment, and predicting prognosis. Accurate FRC measurement can help doctors understand the improvement of gas exchange and ventilation function in the patient's lungs, adjust the treatment plan in a timely manner, and promote better patient recovery.

[0003] Currently, there are various gas washing-in and washing-out methods for measuring residual lung volume (FRC) in patients, such as sulfur hexafluoride washing-in and washing-out. This method does not require invasive procedures (such as bronchoscopy), avoids patient discomfort, and generally uses inert gases that are non-toxic, metabolized quickly, and are suitable for long-term monitoring. However, it is easily affected by patient breathing and airway obstruction, which can lead to a decrease in the accuracy of FRC measurement.

[0004] Based on this, in order to improve detection accuracy, the present invention provides a method for detecting residual lung volume in patients recovering from pneumonia. Summary of the Invention

[0005] To address the problems of the above-mentioned solutions, this invention provides a method for detecting residual lung volume in patients recovering from pneumonia.

[0006] The objective of this invention can be achieved through the following technical solutions: A method for detecting residual lung volume in patients recovering from pneumonia includes: Step 1: Determine the basic detection method, identify the basic information of the basic detection method, perform condition evaluation based on the basic information, obtain the corresponding condition evaluation results, and perform corresponding processing based on the condition evaluation results.

[0007] Furthermore, a condition assessment is conducted based on the basic information, including: Preset condition items and condition criteria; establish a condition evaluation model, the expression of which is: ; In the formula: (TB, si) is the input data, TB is the basic information, i represents the corresponding condition item, i=1, 2, ..., n, n is the number of condition items; si represents the condition standard of the corresponding condition item; TB→si means that the basic information meets the condition standard of the corresponding condition item; the output data is the single evaluation value TP(TB, si), and the single evaluation value is 1 or 0. The basic information and the condition standards of the corresponding condition items are analyzed by the condition evaluation model to obtain the individual evaluation value of the corresponding condition items. When a single evaluation value is 1, the corresponding evaluation condition is qualified. When a single evaluation value is 0, the corresponding condition item is deemed unqualified, and the method of supplementing the condition is determined. The results of the condition evaluation are obtained by summarizing all the conditions.

[0008] Furthermore, determine the methods for supplementing conditions, including: The platform provider shall establish a supplementary reserve warehouse, which shall be used to store the reserve replenishment methods corresponding to the relevant conditions. Identify the condition items that are not qualified, and match the corresponding reserve replenishment method from the replenishment reserve based on the condition items; Prioritize each matching replenishment method to obtain its priority, generate a replenishment recommendation list based on the priority of each replenishment method, display the replenishment recommendation list to the user, and mark the replenishment method selected by the user as a conditional replenishment method.

[0009] Step 2: Assess the patient's airway obstruction and obtain the corresponding airway assessment results; guide the patient to prepare for breathing. Furthermore, guide the patient in preparing for breathing, including: The system presets respiratory standards, monitors patient respiration in real time, and obtains corresponding respiratory monitoring data. It then calibrates the respiratory monitoring data in real time based on the respiratory standards, identifies abnormal respiratory data, and generates corresponding calibration records. These records include whether the respiratory monitoring data for the corresponding time period meets the respiratory standards. Finally, it generates corresponding respiratory adjustment methods based on the abnormal respiratory data and prompts the patient to adjust their breathing according to these methods. A respiratory monitoring chart is generated in real time based on the calibration record. The horizontal axis of the respiratory monitoring chart is time, and the vertical axis is the respiratory abnormal value. The respiratory abnormal value is 1 or 0. A respiratory abnormal value of 1 indicates that the respiratory monitoring data at the corresponding time is abnormal respiratory data, and a respiratory abnormal value of 0 indicates that the respiratory monitoring data at the corresponding time meets the respiratory standard. The patient's respiratory preparation requirements are assessed in real time based on the respiratory monitoring chart. Once the assessment confirms that the respiratory preparation requirements are met, the respiratory preparation is terminated, and the subsequent testing phase begins. If the assessment does not meet the requirements for respiratory preparation, no corresponding procedures should be performed.

[0010] Furthermore, respiratory monitoring charts are generated in real time based on calibration records, including: A respiratory conversion model is established, and its expression is as follows: ; In the formula: LPt represents the calibration result of the respiratory monitoring data at the corresponding time; the output data is the respiratory abnormality value HZ(LPt), and the respiratory abnormality value is 1 or 0; The calibration results corresponding to the time are identified in real time based on the calibration records. The calibration results are then used as input data to the respiratory conversion model for analysis to obtain the respiratory abnormality values ​​at the corresponding time. A respiratory monitoring chart is generated based on the obtained respiratory abnormalities, and the chart is updated in real time based on subsequent respiratory abnormalities.

[0011] Furthermore, the patient's respiratory status is assessed in real time based on the respiratory monitoring chart, including: Determine the breathing preparation requirements, and extract the corresponding preparation features from the breathing monitoring chart in real time based on the breathing preparation requirements; Compare the patient's readiness characteristics with respiratory readiness requirements to determine if the patient meets the requirements.

[0012] Furthermore, the breathing preparation requirement is that the respiratory abnormality value is 0 within a continuous time T and / or the cumulative proportion of time with a respiratory abnormality value of 0 is greater than the threshold X1.

[0013] Step 3: Perform residual volume lung function tests on the patient according to the basic testing method to obtain initial test results. Correct the initial test results based on the airway assessment results to obtain the target monitoring results.

[0014] Furthermore, the initial test results are revised based on the airway assessment results, including: Each patient category is preset, and a corresponding correction model is set for each patient category. The correction model is used to correct the initial detection results of patients within the corresponding patient category. Identify patient information, match a corresponding correction model based on the patient information, and analyze the initial test results and airway assessment results through the correction model to obtain the corresponding target monitoring results.

[0015] Furthermore, during the process of measuring the residual volume of lung function in patients according to the basic testing method, the patient's breathing is monitored in real time to obtain corresponding respiratory monitoring data; and corresponding respiratory monitoring charts are generated based on the respiratory monitoring data. Based on the respiratory monitoring chart, test data corresponding to abnormal periods are removed during the testing process.

[0016] Compared with the prior art, the beneficial effects of the present invention are: Traditional methods for measuring residual lung volume (RLV) based on gas washing (such as sulfur hexafluoride washing) offer advantages such as non-invasive operation, use of inert gases that are non-toxic and rapidly metabolized. However, they are highly susceptible to interference from the patient's respiratory status and airway obstruction, leading to significant deviations in test results and failing to provide doctors with accurate information for lung function assessment. The RLV measurement method for patients recovering from pneumonia provided in this invention effectively overcomes these problems through innovative technical means. It precisely controls and optimizes parameters such as the rate and flow rate of gas washing, maintaining relative stability under different testing environments and reducing interference from external factors. Furthermore, it may incorporate intelligent monitoring and feedback mechanisms to monitor various parameters in real time during the testing process, allowing for timely adjustments upon detecting abnormalities and ensuring the stability of the testing process and the reliability of the results. This provides strong support for doctors to conduct long-term tracking and dynamic assessment of patients' conditions, helping to promptly detect changes in the condition and adjust treatment strategies. Attached Figure Description

[0017] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0018] Figure 1 This is a flowchart of the method of the present invention. Detailed Implementation

[0019] The technical solution of the present invention will be clearly and completely described below with reference to the embodiments. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present invention.

[0020] like Figure 1 As shown, a method for detecting residual lung volume in patients recovering from pneumonia includes: Step 1: Determine the gas wash-in / wash-out method to be used, such as ultrasonic flow meter and sulfur hexafluoride wash-in / wash-out. By inhaling sulfur hexafluoride (SF6) gas of known concentration, its low solubility is utilized to measure the amount of residual gas in the lungs at the end of expiration using a gas analyzer, indirectly calculating the FRC; label the corresponding gas wash-in / wash-out method as the basic detection method; obtain the basic information corresponding to the basic detection method, such as equipment information, process information, etc.; conduct a condition assessment based on the basic information to determine whether it can meet the requirements for subsequent method implementation, mainly referring to respiratory monitoring assessment and airway obstruction detection; obtain the corresponding condition assessment results and perform appropriate processing based on the condition assessment results.

[0021] If it meets the requirements, no further processing is needed. If the necessary equipment or other conditions are lacking, appropriate supplementation should be made or other methods should be used to achieve the desired result.

[0022] In one embodiment, condition evaluation based on basic information includes: Pre-set necessary conditions, and set condition items and condition standards based on the necessary conditions, such as setting condition items and condition standards based on respiratory monitoring assessment and airway obstruction assessment; Establish a conditional evaluation model, the expression of which is: ; In the formula: (TB, si) is the input data, TB is the basic information, i represents the corresponding condition item, i=1, 2, ..., n, n is the number of condition items; si represents the condition standard of the corresponding condition item; TB→si means that the basic information meets the condition standard of the corresponding condition item, and the corresponding training set is labeled with the corresponding historical data for training; the output data is the single evaluation value TP(TB, si), and the single evaluation value is 1 or 0. The basic information and the condition standards of the corresponding condition items are analyzed by the condition evaluation model to obtain the individual evaluation value of the corresponding condition items. When a single evaluation value is 1, the corresponding evaluation condition is qualified. When a single evaluation value is 0, the corresponding condition item is deemed unqualified, and the method of supplementing the condition is determined. The results of the condition evaluation are obtained by summarizing all the conditions.

[0023] In one embodiment, the method of supplementing conditions can be determined based on existing methods, such as commonly used methods such as manually deciding on supplementation devices, applied devices, and methods.

[0024] In one embodiment, determining the condition supplementation method includes: The platform will list various ways to supplement conditions that are not met for the corresponding conditions, mark them as reserve supplement methods, and summarize them to establish a supplement reserve. Identify the condition item that is not qualified, and match the corresponding reserve replenishment method from the replenishment reserve based on the condition item; Prioritize each matching replenishment method to obtain its priority, generate a replenishment recommendation list based on the priority of each replenishment method, display the replenishment recommendation list to the user, and mark the replenishment method selected by the user as a conditional replenishment method.

[0025] Prioritize each matching reserve replenishment method, mainly by taking into account various other conditions available in the scenario. For example, if other devices with corresponding functions can be used for testing, their cost is low and their priority is high. In other words, evaluate the cost and implementation effect of each reserve replenishment method based on the actual situation, and make a comprehensive evaluation priority based on cost and implementation effect. Alternatively, other priority evaluation methods can be used for evaluation.

[0026] In one embodiment, condition assessment can be performed based on basic information, or it can be performed based on existing methods.

[0027] Step 2: Assess the patient's airway obstruction and obtain the corresponding airway assessment results; guide the patient to prepare for breathing, and proceed to the next step after the preparation is completed.

[0028] In one embodiment, patients are assessed for airway obstruction by simultaneously measuring forced expiratory volume (FEV1) and forced expiratory flow (FEF 25%–75%). Airway obstruction is indicated when FEV1 / FVC < 70% or FEF 25%–75% is reduced. Alternatively, the severity of airway obstruction can be graded based on FEV1 / FVC according to guidelines such as the Global Initiative for Chronic Obstructive Lung Disease (GOLD) and the American Thoracic Society (ATS). In other words, existing airway obstruction assessment methods are used for evaluation.

[0029] In one embodiment, guiding a patient through respiratory preparation includes: The system pre-defines respiratory standards for testing based on a standard testing method. For example, the patient performs uniform, deep, and slow breathing (e.g., 4 seconds of inhalation and 6 seconds of exhalation) to form a standard range. The system monitors the patient's breathing in real time to obtain corresponding respiratory monitoring data. It then calibrates the respiratory monitoring data in real time using the respiratory standards, identifying and marking any data that does not meet the standards as abnormal respiratory data. A corresponding calibration record is generated, including whether the respiratory monitoring data for the corresponding time period meets the respiratory standards. Based on the abnormal respiratory data, a corresponding respiratory adjustment method is generated, prompting the patient to adjust their breathing according to the method. A respiratory monitoring chart is generated in real time based on the calibration record. The horizontal axis of the respiratory monitoring chart is time, and the vertical axis is the respiratory abnormal value. The respiratory abnormal value is 1 or 0. A respiratory abnormal value of 1 indicates that the respiratory monitoring data at the corresponding time is abnormal respiratory data, and a respiratory abnormal value of 0 indicates that the respiratory monitoring data at the corresponding time meets the respiratory standard. Real-time assessment of whether respiratory preparation requirements are met based on respiratory monitoring charts; Once the assessment confirms that the breathing preparation requirements are met, breathing preparation is completed, and the subsequent testing phase begins. If the assessment does not meet the requirements for respiratory preparation, no corresponding operation will be performed; instead, respiratory preparation will continue, and breathing adjustments will be made according to the guidance.

[0030] In one embodiment, respiratory monitoring data can be calibrated in real time using respiratory standards, and then compared and evaluated using existing intelligent technologies.

[0031] In one embodiment, a corresponding breathing adjustment method is generated based on abnormal breathing data. This generation is based on existing artificial intelligence technology and is generally done via voice, such as instructing the patient to increase their respiratory rate. For example, a breathing analysis model is built based on a deep learning algorithm. A corresponding training set is manually established for training. The training set includes input data and output data. The input data consists of standard breathing data and abnormal breathing data, while the output data is the breathing adjustment method that changes the current breathing mode to meet the standard breathing mode. The training set is also set using historical data on guiding patients' breathing. The successfully trained breathing analysis model is then used for analysis.

[0032] In one embodiment, generating a respiratory monitoring graph in real time based on calibration records includes: A respiratory conversion model is established, and its expression is as follows: ; In the formula: LPt represents the calibration result of the respiratory monitoring data at the corresponding time; the output data is the respiratory abnormality value HZ(LPt), and the respiratory abnormality value is 1 or 0; The calibration results corresponding to the time are identified in real time based on the calibration records. The calibration results are then used as input data to the respiratory conversion model for analysis to obtain the respiratory abnormality values ​​at the corresponding time. A respiratory monitoring chart is generated based on the obtained respiratory abnormalities, and the chart is updated in real time based on subsequent respiratory abnormalities.

[0033] In one embodiment, the respiratory monitoring chart is used to assess in real time whether the respiratory preparation requirements are met, and the respiratory preparation requirements are determined, such as a respiratory abnormality value of 0 within a continuous time T, or a respiratory abnormality value of 0 being greater than a threshold X1, etc., where T is a positive number; the specific requirements can be set as needed, or a combination of requirements can be set, i.e., multiple requirements can be met simultaneously; the respiratory monitoring chart is used to identify features in real time according to the respiratory preparation requirements to obtain the corresponding preparation features; the preparation features are compared with the respiratory preparation requirements to determine whether the patient meets the respiratory preparation requirements.

[0034] Step 3: Perform residual volume lung function tests on the patient according to the basic testing method to obtain initial test results. Correct the initial test results based on the airway assessment results to obtain the target monitoring results.

[0035] In one embodiment, correcting the initial test results based on airway assessment results includes: The process involves acquiring historical data on airway obstruction using this basic detection method, correcting the results, and classifying patients based on this data. This results into several patient categories that can be corrected using the same method, and can be based on various existing clustering algorithms and classification methods. A corresponding correction model is then built for each patient category, typically using machine learning or deep learning algorithms with self-learning capabilities. This model is trained using a training set labeled with the corresponding historical data. Finally, the corrected model is used for further correction. Identify patient information, match the corresponding patient classification based on the patient information, match the corresponding correction model based on the patient classification, and analyze the initial test results and airway assessment results through the correction model to obtain the corresponding target monitoring results.

[0036] In one embodiment, the initial test results are corrected based on the airway assessment results, which can be done based on existing data correction methods.

[0037] In one embodiment, during the process of measuring the residual volume of lung function in patients according to the basic testing method, the patient's breathing is monitored in real time to obtain corresponding respiratory monitoring data; and a corresponding respiratory monitoring graph is generated based on the respiratory monitoring data. Based on the respiratory monitoring chart, the test data corresponding to the abnormal period are removed during the testing process, that is, the test data of the basic test method for respiratory abnormalities are not analyzed.

[0038] The above formulas are all numerical calculations after removing dimensions. The formulas are obtained by software simulation based on a large amount of data and are closest to the real situation. The preset parameters and preset thresholds in the formulas are set by those skilled in the art according to the actual situation or obtained by simulation based on a large amount of data.

[0039] The above embodiments are only used to illustrate the technical methods of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical methods of the present invention without departing from the spirit and scope of the technical methods of the present invention.

Claims

1. A method for detecting residual lung volume in patients recovering from pneumonia, characterized in that, include: Step 1: Determine the basic detection method, identify the basic information of the basic detection method, perform condition evaluation based on the basic information, obtain the corresponding condition evaluation results, and perform corresponding processing based on the condition evaluation results; Step 2: Assess the patient's airway obstruction and obtain the corresponding airway assessment results; guide the patient to prepare for breathing. Step 3: Perform residual volume lung function tests on the patient according to the basic testing method to obtain initial test results. Correct the initial test results based on the airway assessment results to obtain the target monitoring results.

2. The method for detecting residual lung volume in patients recovering from pneumonia according to claim 1, characterized in that, Based on the basic information, a condition assessment is conducted, including: Preset condition items and condition criteria; establish a condition evaluation model, the expression of which is: ； In the formula: (TB, si) is the input data, TB is the basic information, i represents the corresponding condition item, i=1, 2, ..., n, n is the number of condition items; si represents the condition standard of the corresponding condition item; TB→si means that the basic information meets the condition standard of the corresponding condition item; the output data is the single evaluation value TP(TB, si), and the single evaluation value is 1 or 0. The basic information and the condition standards of the corresponding condition items are analyzed by the condition evaluation model to obtain the individual evaluation value of the corresponding condition items. When a single evaluation value is 1, the corresponding evaluation condition is qualified. When a single evaluation value is 0, the corresponding condition item is deemed unqualified, and the method of supplementing the condition is determined. The results of the condition evaluation are obtained by summarizing all the conditions.

3. The method for detecting residual lung volume in patients recovering from pneumonia according to claim 2, characterized in that, The method for supplementing conditions includes: The platform provider shall establish a supplementary reserve warehouse, which shall be used to store the reserve replenishment methods corresponding to the relevant conditions. Identify the condition items that are not qualified, and match the corresponding reserve replenishment method from the replenishment reserve based on the condition items; Prioritize each matching replenishment method to obtain its priority, generate a replenishment recommendation list based on the priority of each replenishment method, display the replenishment recommendation list to the user, and mark the replenishment method selected by the user as a conditional replenishment method.

4. The method for detecting residual lung volume in patients recovering from pneumonia according to claim 1, characterized in that, Guide the patient in preparing for breathing, including: The system presets respiratory standards, monitors patient respiration in real time, and obtains corresponding respiratory monitoring data. It then calibrates the respiratory monitoring data in real time based on the respiratory standards, identifies abnormal respiratory data, and generates corresponding calibration records. These records include whether the respiratory monitoring data for the corresponding time period meets the respiratory standards. Finally, it generates corresponding respiratory adjustment methods based on the abnormal respiratory data and prompts the patient to adjust their breathing according to these methods. A respiratory monitoring chart is generated in real time based on the calibration record. The horizontal axis of the respiratory monitoring chart is time, and the vertical axis is the respiratory abnormal value. The respiratory abnormal value is 1 or 0. A respiratory abnormal value of 1 indicates that the respiratory monitoring data at the corresponding time is abnormal respiratory data, and a respiratory abnormal value of 0 indicates that the respiratory monitoring data at the corresponding time meets the respiratory standard. The patient's respiratory preparation requirements are assessed in real time based on the respiratory monitoring chart. Once the assessment confirms that the respiratory preparation requirements are met, the respiratory preparation is terminated, and the subsequent testing phase begins. If the assessment does not meet the requirements for respiratory preparation, no corresponding procedures should be performed.

5. The method for detecting residual lung volume in patients recovering from pneumonia according to claim 4, characterized in that, Respiratory monitoring graphs are generated in real time based on calibration records, including: A respiratory conversion model is established, and its expression is as follows: ； In the formula: LPt represents the calibration result of the respiratory monitoring data at the corresponding time; the output data is the respiratory abnormality value HZ(LPt), and the respiratory abnormality value is 1 or 0; The calibration results corresponding to the time are identified in real time based on the calibration records. The calibration results are then used as input data to the respiratory conversion model for analysis to obtain the respiratory abnormality values ​​at the corresponding time. A respiratory monitoring chart is generated based on the obtained respiratory abnormalities, and the chart is updated in real time based on subsequent respiratory abnormalities.

6. The method for detecting residual lung volume in patients recovering from pneumonia according to claim 4, characterized in that, Real-time assessment of whether the patient meets respiratory preparation requirements based on respiratory monitoring charts, including: Determine the breathing preparation requirements, and extract the corresponding preparation features from the breathing monitoring chart in real time based on the breathing preparation requirements; Compare the patient's readiness characteristics with respiratory readiness requirements to determine if the patient meets the requirements.

7. The method for detecting residual lung volume in patients recovering from pneumonia according to claim 6, characterized in that, Breathing preparation requires that the number of respiratory abnormalities is 0 within a continuous time T and / or the cumulative proportion of time with a number of respiratory abnormalities is greater than the threshold X1.

8. The method for detecting residual lung volume in patients recovering from pneumonia according to claim 1, characterized in that, The initial test results were revised based on the airway assessment results, including: Each patient category is preset, and a corresponding correction model is set for each patient category. The correction model is used to correct the initial detection results of patients within the corresponding patient category. Identify patient information, match a corresponding correction model based on the patient information, and analyze the initial test results and airway assessment results through the correction model to obtain the corresponding target monitoring results.

9. The method for detecting residual lung volume in patients recovering from pneumonia according to claim 1, characterized in that, During the process of measuring the residual volume of lung function in patients according to the basic testing method, the patient's breathing is monitored in real time to obtain the corresponding respiratory monitoring data; and the corresponding respiratory monitoring chart is generated based on the respiratory monitoring data. Based on the respiratory monitoring chart, test data corresponding to abnormal periods are removed during the testing process.

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