An artificial intelligence management method and system based on inhalation type drugs

Abstract

The present invention relates to the field of medical care informatics technology, and in particular to an artificial intelligence management method and system based on inhalation-type drugs, including an inhalation capacity evaluation model, an inhalation technology quantitative evaluation model, an inhalation technology training model, and a stable period daily inhalation medication management model that are executed in sequence. The inhalation capacity evaluation model is used to evaluate whether the subject has reached the required inhalation capacity; the inhalation technology quantitative evaluation model is used to evaluate whether the subject's action behavior meets the technical requirements of the inhalation device; the inhalation technology training model uses digital human intelligent interaction technology to simulate and replace the medical staff's teaching and drug interaction scene; the stable period daily inhalation medication management model is used to apply the inhalation technology quantitative evaluation model to the stable period daily inhalation medication management of the subject. The method and system provided by the present invention overcome the standard heterogeneity problem caused by strong subjectivity and reliance on personal experience in the current visual review process of inhalation technology.

Description

Technical Field

[0001] The present invention relates to the technical field of medical care informatics, and in particular to an artificial intelligence management method and system based on inhalation-type drugs. Background Art

[0002] Inhalation therapy is the cornerstone of the treatment of chronic respiratory diseases represented by chronic obstructive pulmonary disease and bronchial asthma. Inhaled drugs are delivered by different devices. Long-term standardized and correct use of inhalation devices can relieve respiratory symptoms, improve exercise tolerance, improve health status, and reduce the risk of acute exacerbations. Surveys and studies have shown that technical errors in the use of inhalation devices are common and lead to poor control of chronic respiratory diseases and increased medical burdens. Guidelines and research evidence both reveal the significant impact of inhalation therapy compliance and inhalation skills on treatment outcomes. It is recommended to provide patients with adequate and appropriate training, regularly review and examine inhalation techniques, improve compliance, and thus serve as a reference for treatment adjustments. Patients' basic ability to use inhalation devices, correct operation of inhalation devices, and regular and quantitative inhalation of drugs are the basis for ensuring efficacy.

[0003] Coordination, dexterity, and hand strength are the basic requirements for using pressure metered-dose aerosols; dry powder inhalers require patients to have a certain inspiratory muscle strength to generate sufficient inspiratory flow rate to deagglomerate the powder aerosol into fine particles <5μm. Maximum inspiratory pressure is an indicator of the patient's inspiratory muscle strength. Gender and age are independent factors. The inspiratory pressure through the inhalation device has a nonlinear relationship with the peak inspiratory flow rate and is considered to be a key indicator of inspiratory capacity. Moreover, the peak inspiratory flow rate through the inhalation device lacks a consistent correlation with the peak inspiratory flow rate measured by the spirometer, so the patient's inspiratory capacity cannot be directly used as a reference for pulmonary ventilation function results. A survey study showed that approximately 23% to 46% of COPD patients have improper peak inspiratory flow rate when using dry powder inhalers. Insufficient peak inspiratory flow rate is common in medium and high resistance inhalation devices, while excessive inspiratory flow rate is more common in low resistance devices. A cross-sectional survey in Europe and Australia recruited more than 1,400 COPD patients who used dry powder inhalers for maintenance treatment. The results showed that compared with the stable period, the inspiratory capacity of COPD patients during the acute exacerbation period decreased by an average of about 20%. In addition, studies have shown that the peak inspiratory flow rate measured through the inhalation device at discharge is an independent factor affecting the 30-day and 90-day re-hospitalization of COPD patients, which may be related to improper use of dry powder inhalers due to insufficient inspiratory capacity. Therefore, the assessment of inhalation capacity can provide some guidance for patients to choose the correct inhalation device.

[0004] Inhalation technique refers to the correctness of each step of the patient's operation when using an inhalation device for inhalation therapy, including device preparation before inhalation, exhalation before inhalation, inhalation speed and method, and breath holding after completing inhalation. There are many factors that affect the patient's inhalation technical performance. The patient's age, educational background, and cognitive impairment affect the inhalation ability and thus affect the inhalation technical performance. Although each inhaled drug has instructions, it is not enough to provide patients with proper education on the use of inhalers. Studies have shown that providing educational interventions on inhalation techniques for patients with COPD and asthma is effective in the short term. The key factors for success include the patient's initial technical mastery and the time that has passed. It is recommended to regularly strengthen interventions and extend the follow-up period.

[0005] Due to the large variety of inhalation devices, the steps and inhalation modes used by different inhalation devices have different technical requirements. Only by mastering good inhalation techniques can the drug be fully delivered and the appropriate aerosol particles are deposited in the lungs to exert their effects. The current inhalation technology training and guidance is mainly based on the experience-dependent model dominated by pharmacists, specialist nurses and other roles. The instructor explains the essentials of inhalation technology to the patient and asks the patient to demonstrate the operation method, and then visually evaluates the patient's mastery of inhalation technology. There is a problem of lack of quantitative standards for inhalation technology evaluation. For example, passive mist-release inhalation devices usually emphasize "quick start, force, and deep inhalation". Even experienced instructors cannot visually evaluate whether the patient's inhalation meets the specific flow rate requirements. Treatment compliance is the degree to which the patient's medication behavior complies with the prescription, which also affects the treatment effect. The current survey on patient medication mainly relies on subjective reports from patients. Whether it is oral reports, medication compliance questionnaires, or issuing diary cards to record medication, there are problems such as omissions and memory bias.

[0006] Medical staff play a central role in the management of inhalation therapy. Best practice evidence recommends that medical staff should consider factors such as the condition, device accessibility, price and reimbursement, ability to use, environmental impact and patient preferences, and select appropriate inhalation devices based on decision-making and sharing mechanisms. Medical staff should be proficient in the correct use requirements and steps of inhaled drugs, provide adequate inhalation technology training, and regularly review patients' inhalation techniques to correct errors. However, in real-world clinical practice, medical staff also have problems with insufficient knowledge of inhalation therapy and insufficient attention, and training for medical staff related to inhalation therapy also needs to be strengthened. Summary of the invention

[0007] The technical problem to be solved by the present invention is to provide an artificial intelligence management method and system for inhalation type drugs, digitally monitor the behavioral data when the inhalation device is used, and establish an inhalation technology analysis model based on comprehensive multi-dimensional data, quantify the key technology requirements for different types of inhalation devices, and determine whether the patient's inhalation technology performance is qualified or meets good standards, thereby overcoming the problems of strong subjectivity, reliance on personal experience and heterogeneous standards in the current visual review process of inhalation technology.

[0008] The present invention is achieved through the following technical solutions:

[0009] An artificial intelligence management method for inhalation-type drugs, including an inhalation capacity evaluation model, an inhalation technology quantitative evaluation model, an inhalation technology training model and a stable period daily inhalation medication management model, the inhalation capacity evaluation model is used to evaluate whether the subject has reached the inhalation capacity required by a passive mist-release inhalation device; the inhalation technology quantitative evaluation model is used to evaluate whether the subject's action behavior when using inhaled drugs meets the technical requirements of the corresponding inhalation device, and identify the category of technical errors; the inhalation technology training model uses digital human intelligent interaction technology to simulate and replace the medical staff's drug teaching interaction scene; the stable period daily inhalation medication management model is used to apply the inhalation technology quantitative evaluation model to the stable period daily inhalation medication management of the subject.

[0010] Furthermore, the artificial intelligence management method for inhalation-type drugs also includes a data statistical display model, which is used to count and display various data generated by the subjects in the inhalation ability assessment model, the inhalation technology quantitative assessment model, the inhalation technology training model and the stable period daily inhalation medication management model.

[0011] Furthermore, the inhalation capacity assessment model includes the following steps:

[0012] S1: The inhalation capacity assessment data acquisition module simulates the internal resistance corresponding to different passive mist release inhalation devices, and collects the inhalation pressure, flow rate and time data from the start to the end of the patient's inhalation under the corresponding internal resistance, and transmits the data to the inhalation capacity assessment and analysis module;

[0013] S2: The inspiratory capacity evaluation and analysis module extracts the maximum inspiratory flow rate and compares it with the minimum inspiratory flow rate and the optimal inspiratory flow rate corresponding to the inhaled drug to evaluate the patient's inspiratory capacity level;

[0014] S3: The inspiratory ability assessment feedback display module converts the collected data and the patient's inspiratory ability level assessment into a visual graphic report to show the inspiratory ability assessment results to the patient.

[0015] Further, in step S2, the patient's inspiratory ability level is evaluated according to the following method: the extracted maximum inspiratory flow rate is compared with the minimum inspiratory flow rate corresponding to the inhaled drug and the optimal inspiratory flow rate; if the maximum inspiratory flow rate is greater than the optimal inspiratory flow rate, it is judged that the patient's inspiratory ability has reached the optimal level; if the maximum inspiratory flow rate is between the minimum inspiratory flow rate and the optimal inspiratory flow rate, it is judged that the patient's inspiratory ability has reached the suboptimal level; if the maximum inspiratory flow rate is less than the minimum inspiratory flow rate, it is judged that the patient's inspiratory ability is insufficient.

[0016] Furthermore, the inhalation technique quantitative assessment model performs a quantitative assessment of the patient's inhalation technique according to the following method:

[0017] The inhalation capacity evaluation model for active mist-release inhalation devices includes the following steps:

[0018] D11: The inhalation technology quantitative evaluation data acquisition module identifies the action and time of starting and loading the medicine and closing and resetting the active mist-release inhalation device, the flow rate data from the start of inhalation to the end of inhalation, and accumulates and calculates the total number of times of starting and loading the medicine;

[0019] D12: The inhalation technology quantitative evaluation data analysis module determines whether the loading action is a valid medication action based on the action and time of starting the loading and closing of the active mist-releasing inhalation device, and proceeds to the next step based on the valid medication action;

[0020] D13: The inhalation technique quantitative assessment data analysis module determines whether the patient's hand-mouth coordination technique is qualified, whether the inspiratory flow rate is appropriate, and whether the patient's deep inhalation technique using an active mist-release inhalation device is qualified;

[0021] D14: If the patient meets the following three conditions at the same time: qualified hand-mouth coordination technique, appropriate inspiratory flow rate, and qualified deep inhalation technique, then the patient is judged to have met the key inhalation technique standards for using an active mist-release inhalation device;

[0022] The inhalation capacity assessment model for passive aerosol inhalation drug delivery devices includes the following steps:

[0023] D21: The data acquisition module for quantitative evaluation of inhalation technology collects the data on the start-up, loading and dispensing, closing and resetting of the passive mist-release inhalation device, the flow rate data from the start to the end of inhalation, and accumulates and calculates the total number of start-up, loading and dispensing actions;

[0024] D22: The inhalation technology quantitative evaluation data analysis module determines whether the loading action is a valid medication action based on the action and time of starting the loading and closing the passive mist-release inhalation device, and proceeds to the next step based on the valid medication action;

[0025] D23: Determine whether the initial acceleration of inhalation of the passive mist-release inhalation device is qualified; whether the inhalation flow rate of the passive mist-release inhalation device is appropriate; whether the patient's deep inhalation technique using the passive mist-release inhalation device is qualified;

[0026] D24: If the patient meets the requirements of qualified initial inhalation acceleration, appropriate inhalation flow rate and qualified deep inhalation technique at the same time, it is judged that the patient has met the key inhalation technique standards for using a passive mist-release inhalation device.

[0027] Further, in step D13, the inhalation technique quantitative evaluation data analysis module determines the hand-mouth coordination technique according to formula (1). If formula (1) is satisfied, it is determined that the hand-mouth coordination technique of the patient using the active mist release inhalation device is qualified; if formula (1) is not satisfied, it is determined that the hand-mouth coordination technique of the patient using the active mist release inhalation device is unqualified.

[0028] (1);

[0029] in: Indicates the time of starting inhalation action. Indicates the start time of loading and drug feeding action. Indicates the time when the inhalation ends. Indicates setting the hand-mouth coordination threshold.

[0030] Optimally, in step D12 or step D22, whether the drug loading action is a valid drug application action is determined according to the following method:

[0031] When the time of the drug loading action is a non-null value and the inhalation duration is greater than or equal to the acceptable inhalation action duration threshold, the drug loading action is judged to be a valid drug administration action. If this condition is not met, the drug loading action is judged to be an invalid drug administration action.

[0032] Optimally, the following method is used in step D13 or step D23 to determine whether the inspiratory flow rate is appropriate:

[0033] The maximum inspiratory flow rate during the inspiratory time period is extracted and compared with the lower limit and upper limit of the inspiratory flow rate set by the inhalation device. If the maximum inspiratory flow rate is greater than the upper limit of the inspiratory flow rate, the inspiratory flow rate is judged to be too high; if the maximum inspiratory flow rate is between the lower limit and the upper limit of the inspiratory flow rate, the inspiratory flow rate is judged to be appropriate; if the maximum inspiratory flow rate is less than the lower limit of the inspiratory flow rate, the inspiratory flow rate is judged to be insufficient.

[0034] Further, in step D13 or step D23, the following method is used to determine whether the deep inhalation technique performance is qualified:

[0035] Extract the effective inspiratory time duration when the inspiratory flow rate is within the range of the inspiratory flow rate lower limit and the inspiratory flow rate upper limit during the inspiratory time period;

[0036] Integrate the inspiratory flow rate during the effective inspiratory time period to obtain the effective inhaled volume;

[0037] The ratio of effective inspired volume to the subjects’ forced vital capacity was calculated;

[0038] According to formula (2), if formula (2) is satisfied, the deep inhalation technique is judged to be qualified; if formula (2) is not satisfied, the deep inhalation technique is judged to be unqualified:

[0039] (2);

[0040] in: Indicates the effective inhalation time. Indicates the inhalation time threshold of the inhalation device. Indicates the effective suction volume, represents the inspiratory volume threshold, represents the forced vital capacity of the subject, Indicates the inspiratory volume ratio threshold.

[0041] Further, in step D23, the following method is used to determine whether the inhalation initial acceleration of the passive mist release inhalation device is qualified:

[0042] The optimal inhalation flow rate during the inhalation period and the time required to reach the optimal inhalation flow rate are extracted, the inhalation starting acceleration is calculated, and the inhalation starting acceleration is compared with the inhalation starting acceleration setting threshold. If the calculated inhalation starting acceleration is greater than or equal to the inhalation starting acceleration setting threshold, the inhalation starting acceleration used by the passive mist release inhalation device is judged to be qualified. If the calculated inhalation starting acceleration is less than the inhalation starting acceleration setting threshold, the inhalation starting acceleration used by the passive mist release inhalation device is judged to be unqualified.

[0043] Further, the inhalation technique training model comprises the following steps:

[0044] E1: The virtual digital human animation demonstrates the use steps of various types of inhalation devices and the technical requirements of each step. The patient watches the digital human animation demonstration and uses the inhalation drug device according to the operating instructions;

[0045] E2: The inhalation technique training and detection module determines whether the patient's inhalation technique performance using the inhalation device meets the standard based on the inhalation technique quantitative evaluation model, and indicates the category of inhalation technique errors when the inhalation technique performance does not meet the standard;

[0046] E3: The enhanced feedback module for inhalation technique training displays the patient's inhalation technique performance to the operator and the patient and generates an evaluation report. Based on the feedback, the patient's behavioral movements for using the inhalation device are repeatedly trained until the inhalation technique performance meets the standard.

[0047] Furthermore, the daily inhalation medication management model during the stable period includes the following steps:

[0048] F1: The daily inhalation medication management detection module in the stable period determines the number of effective inhalation medication actions of the patient during the planned medication period according to the inhalation technology quantitative evaluation model, and determines whether there is over-use or under-use according to the set inhalation medication plan frequency; and determines whether the key inhalation technology of each inhalation medication action meets the standard, and calculates the standard-reaching rate, error rate and error classification of key inhalation technology during the medication plan;

[0049] F2: The data analysis module for daily inhalation medication management in the stable period calculates the actual inhalation medication compliance by comprehensively considering the actual medication frequency during the medication plan and the performance of key inhalation techniques;

[0050] F3: The enhanced feedback module for daily inhalation medication management during the stable period uses visual charts to display the technical performance of each inhalation medication, and generates trend charts and reports; at the same time, it reminds and intervenes in the patient's medication.

[0051] Optimized, in step F3, the actual inhalation medication compliance is calculated according to formula (3): :

[0052] (3);

[0053] in: Indicates the actual number of medications taken during the planned medication period. The proportion of patients who performed the inhalation technique correctly during the planned medication period, Indicates the total number of planned medication doses.

[0054] Optimized, the data statistics display model includes the following steps:

[0055] G1: The data statistics module classifies and counts the data generated by the inhalation capacity assessment model, the inhalation technology quantitative assessment model, the inhalation technology training model, and the daily inhalation medication management model in the stable period, and performs secondary processing to form charts;

[0056] G2: The data display module summarizes and displays data in the form of charts.

[0057] An artificial intelligence management system for inhalation-type drugs, used to execute any of the artificial intelligence management methods for inhalation-type drugs described above, which includes an inhalation ability assessment unit, an inhalation technology quantitative assessment unit, an inhalation technology training unit and a stable period daily inhalation management unit connected in sequence, the inhalation ability assessment unit is used to assess whether the subject has achieved the inhalation ability required by the passive mist release inhalation device; the inhalation technology quantitative assessment unit is used to assess whether the subject's action behavior when using inhaled drugs meets the technical requirements of the inhalation device, and identify the category of technical errors; the inhalation technology training unit uses digital human intelligent interaction technology to simulate and replace the medical staff's drug teaching interaction scene; the stable period daily inhalation management unit is used to apply the inhalation technology quantitative assessment model to the subject's stable period daily inhalation medication management.

[0058] Furthermore, the inhalation ability assessment unit includes an inhalation ability assessment data acquisition module, an inhalation ability assessment analysis module and an inhalation ability assessment feedback display module; the inhalation technology quantitative assessment unit includes an inhalation technology quantitative assessment data acquisition module and an inhalation technology quantitative assessment data analysis module; the inhalation technology training unit includes a virtual digital human, an inhalation technology training detection module and an inhalation technology training enhanced feedback module; the stable period daily inhalation management unit includes a stable period daily inhalation medication management detection module, a scale collection module, a stable period daily inhalation medication management data analysis module and a stable period daily inhalation medication management enhanced feedback module.

[0059] Furthermore, an artificial intelligence management system based on inhalation type drugs also includes a data statistics display unit, which includes a data statistics module and a data display module.

[0060] Beneficial effects of the invention:

[0061] The present invention provides an artificial intelligence management method and system for inhalation-type drugs, which performs digital monitoring based on the behavioral data when the inhalation device is used, and establishes an inhalation technology analysis model that integrates multi-dimensional data, quantifies the key technologies required for different types of inhalation devices, and thus determines whether the patient's inhalation technology performance is qualified or reaches a good standard. It extracts and quantifies parameters such as hand-mouth coordination, inspiratory flow rate, inspiratory acceleration, and inspiratory volume, overcomes the problem of strong subjectivity and heterogeneity of standards in the current visual review of inhalation technology; similarly, in the long-term management of chronic respiratory diseases, reliable "real compliance" is obtained, which greatly reduces the omission of patient reports and the problem of inaccurate information caused by memory bias. The system can enhance the patient's self-management ability and provide reliable information for medical staff to formulate optimized treatment management strategies. The digital technology solution is based on wireless data transmission and remote service response, has fewer requirements for users, and is more friendly to the group of patients with chronic respiratory diseases with an average age of older, which can improve the accessibility of chronic disease populations to high-quality management services and improve the management efficiency of medical staff. The present invention not only feeds back results in the form of system notifications, but also uses intelligent outbound calling technology to solve the problem that the elderly do not have smart phones or do not know how to use smart phones, allowing users to use system functions without mobile phone applications. BRIEF DESCRIPTION OF THE DRAWINGS

[0062] Figure 1 It is the overall flow chart of the present invention.

[0063] Figure 2 It is a flow chart of the air intake capacity evaluation model of the present invention.

[0064] Figure 3 It is a flow chart of the quantitative evaluation model of the inhalation technology of the active mist-releasing inhalation device of the present invention.

[0065] Figure 4 It is a flow chart of the quantitative evaluation model of the inhalation technology of the passive mist-release inhalation drug delivery device of the present invention.

[0066] Figure 5 It is a flow chart of the inhalation technique training model of the present invention.

[0067] Figure 6 It is a flow chart of the daily inhalation medication management model during the stable period of the present invention. DETAILED DESCRIPTION

[0068] An artificial intelligence management method for inhaled drugs, the overall flow chart is as follows Figure 1As shown, it includes an inhalation capacity evaluation model, an inhalation technique quantitative evaluation model, an inhalation technique training model and a stable period daily inhalation medication management model, which are performed in sequence. The inhalation capacity evaluation model is used to evaluate whether the subject has achieved the inhalation capacity required by the passive mist release inhalation device; the inhalation technique quantitative evaluation model is used to evaluate whether the subject's action behavior when using the inhaled drug meets the technical requirements of the corresponding type of inhalation device, and identify the category of technical errors; the inhalation technique training model uses digital human intelligent interaction technology to simulate and replace the medical staff's drug teaching interaction scene; the stable period daily inhalation medication management model is used to apply the inhalation technique quantitative evaluation model to the subject's stable period daily inhalation medication management.

[0069] The present invention provides an artificial intelligence management method for inhalation-type drugs, which performs digital monitoring based on the behavioral data when the inhalation device is used, and establishes an inhalation technology analysis model based on comprehensive multi-dimensional data, and quantifies the key technology requirements for different types of inhalation devices, thereby determining whether the patient's inhalation technology performance is qualified or meets good standards.

[0070] This method can enhance patients' self-management ability and provide reliable information for medical staff to develop optimized treatment management strategies. Digital technology solutions based on wireless data transmission and remote service response have fewer requirements on users, especially for chronic respiratory disease patients with an average age of older, which can improve the accessibility of chronic disease patients to high-quality management services and improve the management efficiency of medical staff.

[0071] Furthermore, the method based on artificial intelligence management of inhalation-type drugs also includes a data statistical display model, which is used to count and display various data generated by the subjects in the inhalation ability assessment model, the inhalation technology quantitative assessment model, the inhalation technology training model and the stable period daily inhalation medication management model.

[0072] The types of inhalation devices include pressure-metered metered-dose aerosol inhalation devices, soft mist inhalation devices and dry powder inhalation devices. Among them, pressure-metered metered-dose aerosol inhalation devices and soft mist inhalation devices are active mist-release inhalation devices, and dry powder inhalation devices are passive mist-release inhalation devices. The inhalation ability assessment model is mainly used to assess the patient's inhalation ability when using a passive mist-release inhalation device.

[0073] According to the type of inhalation device, the inhalation capacity evaluation data acquisition module includes a digital sensor for a pressure quantitative aerosol inhalation device, a digital sensor for a dry powder inhalation device, and a digital sensor for a soft mist inhalation device. The actions of identifying the inhalation device to start loading medicine and shut down and reset can use a resistive pressure sensor element and an inductive switch element.

[0074] Specifically, the flow chart of the inhalation capacity evaluation model is as follows: Figure 2As shown, the following steps are included:

[0075] S1: The inhalation capacity assessment data acquisition module simulates the internal resistance corresponding to different passive mist release inhalation devices, and collects the inhalation pressure, flow rate and time data from the start to the end of the patient's inhalation under the corresponding internal resistance, and transmits the data to the inhalation capacity assessment and analysis module;

[0076] S2: The inspiratory capacity evaluation and analysis module extracts the maximum inspiratory flow rate and compares it with the minimum inspiratory flow rate and the optimal inspiratory flow rate corresponding to the inhaled drug to evaluate the patient's inspiratory capacity level;

[0077] Specifically, the patient's inspiratory ability level can be evaluated according to the following method: compare the extracted maximum inspiratory flow rate with the minimum inspiratory flow rate corresponding to the inhaled drug and the optimal inspiratory flow rate; if the maximum inspiratory flow rate is greater than the optimal inspiratory flow rate, it is judged that the patient's inspiratory ability has reached the optimal level; if the maximum inspiratory flow rate is between the minimum inspiratory flow rate and the optimal inspiratory flow rate, it is judged that the patient's inspiratory ability has reached the suboptimal level; if the maximum inspiratory flow rate is less than the minimum inspiratory flow rate, it is judged that the patient's inspiratory ability is insufficient.

[0078] The values ​​of the minimum inspiratory flow rate and the optimal inspiratory flow rate corresponding to the inhaled drug are determined by the characteristics of the passive mist-release inhalation device and can be set in advance in the program.

[0079] S3: The inspiratory ability assessment feedback display module converts the collected data and the patient's inspiratory ability level assessment into a visual graphic report to show the inspiratory ability assessment results to the patient.

[0080] The inhalation capacity assessment model is based on digital monitoring of behavioral data when using a passive mist-release inhalation device.

[0081] The maximum inspiratory flow rate is extracted and compared with the minimum inspiratory flow rate and the optimal inspiratory flow rate corresponding to the inhaled drug to evaluate whether the subject has achieved the inspiratory capacity required by the passive mist-release inhalation device, thereby accurately evaluating the patient's inspiratory capacity level.

[0082] If the evaluation result shows that the patient's inhalation ability reaches the optimal level or the suboptimal level, it is judged that the patient's inhalation ability is suitable for using a simulated passive mist-release inhalation device, and the evaluation proceeds to the next step. If the evaluation result shows that the patient's inhalation ability is insufficient, it is necessary to train the patient to improve his inhalation ability and then conduct the evaluation according to the above steps, or directly replace it with another type of inhalation device.

[0083] Through the above method, the patient's behavioral data when using the inhalation device is first digitally monitored, and the key technologies required for different types of inhalation devices are quantified, so as to determine the patient's inhalation ability, and then determine what specific measures to take based on the judgment results. It overcomes the current problem of strong subjectivity, reliance on personal experience and heterogeneous standards in the visual review process of inhalation technology; it can enhance the patient's self-management ability and provide reliable information for medical staff to formulate optimized treatment management strategies.

[0084] Furthermore, the inhalation technique quantitative assessment model performs a quantitative assessment of the patient's inhalation technique according to the following method:

[0085] The flow chart of the inhalation capacity evaluation model for active mist-releasing inhalation devices is as follows: Figure 3 As shown, the following steps are included:

[0086] D11: The inhalation technology quantitative evaluation data acquisition module identifies the action and time of starting and loading the medicine and closing and resetting the active mist-release inhalation device, the flow rate data from the start of inhalation to the end of inhalation, and accumulates and calculates the total number of times of starting and loading the medicine;

[0087] D12: The inhalation technology quantitative evaluation data analysis module determines whether the loading action is a valid medication action based on the action and time of starting the loading and closing of the active mist-releasing inhalation device, and proceeds to the next step based on the valid medication action;

[0088] Specifically, whether the drug loading action is a valid drug application action can be determined according to the following method:

[0089] When the time of the drug loading action is a non-null value and the inhalation duration is greater than or equal to the acceptable inhalation action duration threshold, the drug loading action is judged to be a valid drug administration action. If this condition is not met, the drug loading action is judged to be an invalid drug administration action.

[0090] D13: The inhalation technique quantitative assessment data analysis module determines whether the patient's hand-mouth coordination technique is qualified, whether the inspiratory flow rate is appropriate, and whether the patient's deep inhalation technique using an active mist-release inhalation device is qualified;

[0091] Specifically, the inhalation technique quantitative evaluation data analysis module can judge the hand-mouth coordination technique according to formula (1). If formula (1) is satisfied, it is judged that the hand-mouth coordination technique of the patient using the active mist-release inhalation device is qualified; if formula (1) is not satisfied, it is judged that the hand-mouth coordination technique of the patient using the active mist-release inhalation device is unqualified.

[0092] (1);

[0093] in: Indicates the time of starting inhalation action. Indicates the start time of loading and drug feeding action. Indicates the time when the inhalation ends. Indicates setting the hand-mouth coordination threshold.

[0094] The following methods can be used to determine whether the inspiratory flow rate is appropriate:

[0095] The maximum inspiratory flow rate during the inspiratory time period is extracted and compared with the lower limit and upper limit of the inspiratory flow rate set by the inhalation device. If the maximum inspiratory flow rate is greater than the upper limit of the inspiratory flow rate, the inspiratory flow rate is judged to be too high; if the maximum inspiratory flow rate is between the lower limit and the upper limit of the inspiratory flow rate, the inspiratory flow rate is judged to be appropriate; if the maximum inspiratory flow rate is less than the lower limit of the inspiratory flow rate, the inspiratory flow rate is judged to be insufficient.

[0096] Specifically, the following methods can be used to determine whether the deep inhalation technique performance is qualified:

[0097] Extract the effective inspiratory time duration when the inspiratory flow rate is within the range of the inspiratory flow rate lower limit and the inspiratory flow rate upper limit during the inspiratory time period;

[0098] Integrate the inspiratory flow rate during the effective inspiratory time period to obtain the effective inhaled volume;

[0099] The ratio of effective inspired volume to the subjects’ forced vital capacity was calculated;

[0100] According to formula (2), if formula (2) is satisfied, the deep inhalation technique is judged to be qualified; if formula (2) is not satisfied, the deep inhalation technique is judged to be unqualified:

[0101] (2);

[0102] in: Indicates the effective inhalation time. Indicates the inhalation time threshold of the inhalation device. Indicates the effective suction volume, represents the inspiratory volume threshold, represents the forced vital capacity of the subject, Indicates the inspiratory volume ratio threshold.

[0103] D14: If the patient meets the following three conditions at the same time: qualified hand-mouth coordination technique, appropriate inspiratory flow rate, and qualified deep inhalation technique, then the patient is judged to have met the key inhalation technique standards for using an active mist-release inhalation device;

[0104] The flow chart of the inhalation capacity evaluation model for passive mist-release inhalation drug delivery devices is as follows: Figure 4 As shown, the following steps are included:

[0105] D21: The data acquisition module for quantitative evaluation of inhalation technology collects the data on the start-up, loading and dispensing, closing and resetting of the passive mist-release inhalation device, the flow rate data from the start to the end of inhalation, and accumulates and calculates the total number of start-up, loading and dispensing actions;

[0106] D22: The inhalation technology quantitative evaluation data analysis module determines whether the loading action is a valid medication action based on the action and time of starting the loading and closing the passive mist-release inhalation device, and proceeds to the next step based on the valid medication action;

[0107] Specifically, whether the drug loading action is a valid drug application action can be determined according to the following method:

[0108] When the time of the drug loading action is a non-null value and the inhalation duration is greater than or equal to the acceptable inhalation action duration threshold, the drug loading action is judged to be a valid drug administration action. If this condition is not met, the drug loading action is judged to be an invalid drug administration action.

[0109] D23: Determine whether the initial acceleration of inhalation of the passive mist-release inhalation device is qualified; whether the inhalation flow rate of the passive mist-release inhalation device is appropriate; whether the patient's deep inhalation technique using the passive mist-release inhalation device is qualified;

[0110] Specifically, the following methods can be used to determine whether the inspiratory flow rate is appropriate:

[0111] The maximum inspiratory flow rate during the inspiratory time period is extracted and compared with the lower limit and upper limit of the inspiratory flow rate set by the inhalation device. If the maximum inspiratory flow rate is greater than the upper limit of the inspiratory flow rate, the inspiratory flow rate is judged to be too high; if the maximum inspiratory flow rate is between the lower limit and the upper limit of the inspiratory flow rate, the inspiratory flow rate is judged to be appropriate; if the maximum inspiratory flow rate is less than the lower limit of the inspiratory flow rate, the inspiratory flow rate is judged to be insufficient.

[0112] Specifically, the following methods can be used to determine whether the deep inhalation technique performance is qualified:

[0113] Extract the effective inspiratory time duration when the inspiratory flow rate is within the range of the inspiratory flow rate lower limit and the inspiratory flow rate upper limit during the inspiratory time period;

[0114] Integrate the inspiratory flow rate during the effective inspiratory time period to obtain the effective inhaled volume;

[0115] The ratio of effective inspired volume to the subjects’ forced vital capacity was calculated;

[0116] According to formula (2), if formula (2) is satisfied, the deep inhalation technique is judged to be qualified; if formula (2) is not satisfied, the deep inhalation technique is judged to be unqualified:

[0117] (2);

[0118] in: Indicates the effective inhalation time. Indicates the inhalation time threshold of the inhalation device. Indicates the effective suction volume, represents the inspiratory volume threshold, represents the forced vital capacity of the subject, Indicates the inspiratory volume ratio threshold.

[0119] Specifically, the following method can be used to determine whether the initial acceleration of inhalation of a passive mist-releasing inhalation device is qualified:

[0120] The optimal inhalation flow rate during the inhalation period and the time required to reach the optimal inhalation flow rate are extracted, the inhalation starting acceleration is calculated, and the inhalation starting acceleration is compared with the inhalation starting acceleration setting threshold. If the calculated inhalation starting acceleration is greater than or equal to the inhalation starting acceleration setting threshold, the inhalation starting acceleration used by the passive mist release inhalation device is judged to be qualified. If the calculated inhalation starting acceleration is less than the inhalation starting acceleration setting threshold, the inhalation starting acceleration used by the passive mist release inhalation device is judged to be unqualified.

[0121] D24: If the patient meets the requirements of qualified initial acceleration of inhalation, appropriate inspiratory flow rate, and qualified deep inhalation technique at the same time, it is judged that the patient has met the key inhalation technique standards for using a passive mist-release inhalation device.

[0122] The quantitative evaluation model for inhalation technique conducts quantitative evaluation of inhalation technique according to the characteristics of passive mist-release inhalation devices and active mist-release inhalation devices. For active mist-release inhalation devices, the inhalation capacity is evaluated mainly from three aspects: hand-mouth coordination technical performance, inspiratory flow rate, and deep inhalation technical performance. For passive mist-release inhalation devices, the inhalation capacity is evaluated mainly from three aspects: qualified inhalation starting acceleration, appropriate inspiratory flow rate, and deep inhalation technical performance. This further overcomes the problems of strong subjectivity, reliance on personal experience, and heterogeneous standards in the current visual review process of inhalation technique.

[0123] Further, the inhalation technique training model flow chart is as follows Figure 5 As shown, the following steps are included:

[0124] E1: The virtual digital human animation demonstrates the use steps of various types of inhalation devices and the technical requirements of each step. The patient watches the digital human animation demonstration and uses the inhalation drug device according to the operating instructions;

[0125] E2: The inhalation technique training and detection module determines whether the patient's inhalation technique performance using the inhalation device meets the standard based on the inhalation technique quantitative evaluation model, and indicates the category of inhalation technique errors when the inhalation technique performance does not meet the standard;

[0126] E3: The enhanced feedback module for inhalation technique training displays the patient's inhalation technique performance to the operator and the patient and generates an evaluation report. Based on the feedback, the patient's behavioral movements for using the inhalation device are repeatedly trained until the inhalation technique performance meets the standard.

[0127] The details can be presented to the operator and the patient through voice and animation interaction.

[0128] The inhalation technology training model uses virtual digital human animation to demonstrate the use steps of various types of inhalation devices and the technical requirements of each step to provide targeted guidance on the use of inhalation drug devices. It also uses the inhalation technology quantitative evaluation model to determine whether the patient's inhalation technology performance using the inhalation device meets the standards, further improving the patient's inhalation skills and benefiting the efficacy of inhaled drugs.

[0129] Further, the flow chart of the daily inhalation medication management model during the stable period is as follows: Figure 6 As shown, the following steps are included:

[0130] F1: The daily inhalation medication management detection module in the stable period determines the number of effective inhalation medication actions of the patient during the planned medication period according to the inhalation technology quantitative evaluation model, and determines whether there is over-use or under-use according to the set inhalation medication plan frequency; and determines whether the key inhalation technology of each inhalation medication action meets the standard, and calculates the standard-reaching rate, error rate and error classification of key inhalation technology during the medication plan;

[0131] F2: The data analysis module for daily inhalation medication management in the stable period calculates the actual inhalation medication compliance by comprehensively considering the actual medication frequency during the medication plan and the performance of key inhalation techniques;

[0132] Specifically, the actual inhalation medication compliance can be calculated according to formula (3): :

[0133] (3);

[0134] in: Indicates the actual number of medications taken during the planned medication period. The proportion of patients who performed the inhalation technique correctly during the planned medication period, Indicates the total number of planned medication doses.

[0135] F3: The enhanced feedback module for daily inhalation medication management during the stable period uses visual charts to display the technical performance of each inhalation medication, and generates trend charts and reports; at the same time, it reminds and intervenes in the patient's medication.

[0136] Specifically, the enhanced feedback module for daily inhalation medication management in the stable period uses text, voice, and smart phone to remind intervention subjects according to the situation. The reminders or interventions include the categories of inhalation technical errors, methods to correct errors, the hazards of low inhalation medication compliance, and other educational content related to inhalation therapy.

[0137] The categories of inhalation technical errors include over- or under-use that does not comply with the planned frequency of inhalation medication, the proportion of inhalation technical errors exceeding the set warning threshold, and the actual percentage of inhalation medication compliance being lower than the set warning threshold.

[0138] The daily inhalation medication management model in the stable period obtains reliable "true compliance" in the long-term management of chronic respiratory diseases, greatly reducing the problem of inaccurate information caused by omissions in patient reports and memory bias. The system can enhance patients' self-management capabilities and provide reliable information for medical staff to formulate optimized treatment management strategies. Digital technology solutions can be based on wireless data transmission and remote service response, with fewer requirements for users, especially for chronic respiratory disease patients with an average older age. It can improve the accessibility of high-quality management services for chronic disease populations and improve the management efficiency of medical staff. In addition to the form of system notifications, the present invention also uses intelligent outbound calling technology to feedback results to solve the problem that the elderly do not have smartphones or cannot use smartphones, allowing users to use system functions without mobile phone applications.

[0139] Optimized, the data statistics display model includes the following steps:

[0140] G1: The data statistics module classifies and counts the data generated by the inhalation capacity assessment model, the inhalation technology quantitative assessment model, the inhalation technology training model, and the daily inhalation medication management model in the stable period, and performs secondary processing to form charts;

[0141] G2: The data display module summarizes and displays data in the form of charts.

[0142] An artificial intelligence management system for inhalation-type drugs, used to execute any of the artificial intelligence management methods for inhalation-type drugs described above, which includes an inhalation ability assessment unit, an inhalation technology quantitative assessment unit, an inhalation technology training unit and a stable period daily inhalation management unit connected in sequence, the inhalation ability assessment unit is used to assess whether the subject has achieved the inhalation ability required by the passive mist release inhalation device; the inhalation technology quantitative assessment unit is used to assess whether the subject's action behavior when using inhaled drugs meets the technical requirements of the inhalation device, and identify the category of technical errors; the inhalation technology training unit uses digital human intelligent interaction technology to simulate and replace the medical staff's drug teaching interaction scene; the stable period daily inhalation management unit is used to apply the inhalation technology quantitative assessment model to the subject's stable period daily inhalation medication management.

[0143] Furthermore, the inhalation ability assessment unit includes an inhalation ability assessment data acquisition module, an inhalation ability assessment analysis module and an inhalation ability assessment feedback display module; the inhalation technology quantitative assessment unit includes an inhalation technology quantitative assessment data acquisition module and an inhalation technology quantitative assessment data analysis module; the inhalation technology training unit includes a virtual digital human, an inhalation technology training detection module and an inhalation technology training enhanced feedback module; the stable period daily inhalation management unit includes a stable period daily inhalation medication management detection module, a scale collection module, a stable period daily inhalation medication management data analysis module and a stable period daily inhalation medication management enhanced feedback module.

[0144] Furthermore, an artificial intelligence management system based on inhalation type drugs also includes a data statistics display unit, which includes a data statistics module and a data display module.

[0145] In summary, the present invention provides an artificial intelligence management method and system for inhalation-type drugs, which digitally monitors the behavioral data when the inhalation device is used, and establishes an inhalation technology analysis model based on comprehensive multi-dimensional data. It quantifies the key technologies required for different types of inhalation devices and determines whether the patient's inhalation technology performance is qualified or meets good standards, overcoming the problems of strong subjectivity, reliance on personal experience and heterogeneous standards in the current visual review process of inhalation technology.

[0146] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. An artificial intelligence management method for inhaled drugs, characterized by: It includes an inhalation capacity assessment model, an inhalation technique quantitative assessment model, an inhalation technique training model and a stable period daily inhalation medication management model, which are performed in sequence. The inhalation capacity assessment model is used to assess whether the subject has reached the inhalation capacity required by the passive mist release inhalation device; the inhalation technique quantitative assessment model is used to assess whether the subject's action behavior when using the inhaled drug meets the technical requirements of the corresponding inhalation device, and to identify the category of technical errors; the inhalation technique training model uses digital human intelligent interaction technology to simulate and replace the medical staff's interactive teaching scene; the stable period daily inhalation medication management model is used to apply the inhalation technique quantitative assessment model to the stable period daily inhalation medication management of the subject; The inhalation capacity evaluation model comprises the following steps: S1: The inhalation capacity assessment data acquisition module simulates the internal resistance corresponding to different passive mist release inhalation devices, and collects the inhalation pressure, flow rate and time data from the start to the end of the patient's inhalation under the corresponding internal resistance, and transmits the data to the inhalation capacity assessment and analysis module; S2: The inspiratory capacity evaluation and analysis module extracts the maximum inspiratory flow rate and compares it with the minimum inspiratory flow rate and the optimal inspiratory flow rate corresponding to the inhaled drug to evaluate the patient's inspiratory capacity level; S3: The inspiratory capacity assessment feedback display module forms a visual graphic report of the collected data and the patient's inspiratory capacity level assessment, and displays the inspiratory capacity assessment results to the patient; The inhalation technique quantitative assessment model performs a quantitative assessment of the patient's inhalation technique according to the following method: The inhalation capacity evaluation model for active mist-release inhalation devices includes the following steps: D11: The inhalation technology quantitative evaluation data acquisition module identifies the action and time of starting and loading the medicine and closing and resetting the active mist-release inhalation device, the flow rate data from the start of inhalation to the end of inhalation, and accumulates and calculates the total number of times of starting and loading the medicine; D12: The inhalation technology quantitative evaluation data analysis module determines whether the loading action is a valid medication action based on the action and time of starting the loading and closing of the active mist-releasing inhalation device, and proceeds to the next step based on the valid medication action; D13: The inhalation technique quantitative assessment data analysis module determines whether the patient's hand-mouth coordination technique is qualified, whether the inspiratory flow rate is appropriate, and whether the patient's deep inhalation technique using an active mist-release inhalation device is qualified; D14: If the patient meets the following three conditions at the same time: qualified hand-mouth coordination technique, appropriate inspiratory flow rate, and qualified deep inhalation technique, then the patient is judged to have met the key inhalation technique standards for using an active mist-release inhalation device; The inhalation capacity assessment model for passive aerosol inhalation drug delivery devices includes the following steps: D21: The data acquisition module for quantitative evaluation of inhalation technology collects the data on the start-up, loading and dispensing, closing and resetting of the passive mist-release inhalation device, the flow rate data from the start to the end of inhalation, and accumulates and calculates the total number of start-up, loading and dispensing actions; D22: The inhalation technology quantitative evaluation data analysis module determines whether the loading action is a valid medication action based on the action and time of starting the loading and closing the passive mist-release inhalation device, and proceeds to the next step based on the valid medication action; D23: Determine whether the initial acceleration of inhalation of the passive mist-release inhalation device is qualified; whether the inhalation flow rate of the passive mist-release inhalation device is appropriate; whether the patient's deep inhalation technique using the passive mist-release inhalation device is qualified; D24: If the patient meets the requirements of qualified initial acceleration of inhalation, appropriate inhalation flow rate, and qualified deep inhalation technique at the same time, it is determined that the patient has met the key inhalation technique standards for using a passive mist-release inhalation device; The stable period daily inhalation medication management model includes the following steps: F1: The daily inhalation medication management detection module in the stable period determines the number of effective inhalation medication actions of the patient during the planned medication period according to the inhalation technology quantitative evaluation model, and determines whether there is over-use or under-use according to the set inhalation medication plan frequency; and determines whether the key inhalation technology of each inhalation medication action meets the standard, and calculates the standard-reaching rate, error rate and error classification of key inhalation technology during the medication plan; F2: The data analysis module for daily inhalation medication management in the stable period calculates the actual inhalation medication compliance based on the actual medication frequency during the medication plan and the performance of key inhalation techniques; F3: The enhanced feedback module for daily inhalation medication management during the stable period uses visual charts to display the technical performance of each inhalation medication, and generates trend charts and reports; at the same time, it reminds and intervenes in the patient's medication.

2. The artificial intelligence management method for inhaled drugs according to claim 1, characterized in that: It also includes a data statistics display model, which is used to count and display various data generated by the subjects in the inhalation ability evaluation model, the inhalation technology quantitative evaluation model, the inhalation technology training model and the stable period daily inhalation medication management model.

3. The artificial intelligence management method for inhalation-type drugs according to claim 1 is characterized in that: In step S2, the patient's inspiratory ability level is evaluated according to the following method: the extracted maximum inspiratory flow rate is compared with the minimum inspiratory flow rate corresponding to the inhaled drug and the optimal inspiratory flow rate. If the maximum inspiratory flow rate is greater than the optimal inspiratory flow rate, it is judged that the patient's inspiratory ability has reached the optimal level. If the maximum inspiratory flow rate is between the minimum inspiratory flow rate and the optimal inspiratory flow rate, it is judged that the patient's inspiratory ability has reached the suboptimal level. If the maximum inspiratory flow rate is less than the minimum inspiratory flow rate, it is judged that the patient's inspiratory ability is insufficient.

4. The artificial intelligence management method for inhalation-type drugs according to claim 1 is characterized in that: In step D13, the inhalation technique quantitative evaluation data analysis module determines the hand-mouth coordination technique according to formula (1). If formula (1) is satisfied, it is determined that the hand-mouth coordination technique of the patient using the active mist release inhalation device is qualified; if formula (1) is not satisfied, it is determined that the hand-mouth coordination technique of the patient using the active mist release inhalation device is unqualified. （1）； in: Indicates the time of starting inhalation action. Indicates the start time of loading and drug feeding action. Indicates the time when the inhalation ends. Indicates setting the hand-mouth coordination threshold.

5. The artificial intelligence management method for inhalation-type drugs according to claim 1 is characterized in that: In step D12 or step D22, whether the drug loading action is a valid drug application action is determined according to the following method: When the time of the drug loading action is a non-null value and the inhalation duration is greater than or equal to the acceptable inhalation action duration threshold, the drug loading action is judged to be a valid drug administration action. If this condition is not met, the drug loading action is judged to be an invalid drug administration action.

6. The artificial intelligence management method for inhalation-type drugs according to claim 1 is characterized in that: In step D13 or step D23, the following method is used to determine whether the inspiratory flow rate is appropriate: The maximum inspiratory flow rate during the inspiratory time period is extracted and compared with the lower limit and upper limit of the inspiratory flow rate set by the inhalation device. If the maximum inspiratory flow rate is greater than the upper limit of the inspiratory flow rate, the inspiratory flow rate is judged to be too high; if the maximum inspiratory flow rate is between the lower limit and the upper limit of the inspiratory flow rate, the inspiratory flow rate is judged to be appropriate; if the maximum inspiratory flow rate is less than the lower limit of the inspiratory flow rate, the inspiratory flow rate is judged to be insufficient.

7. The artificial intelligence management method for inhalation-type drugs according to claim 1 is characterized in that: In step D13 or step D23, the following method is used to determine whether the deep inhalation technique performance is qualified: Extract the effective inspiratory time duration when the inspiratory flow rate is within the range of the inspiratory flow rate lower limit and the inspiratory flow rate upper limit during the inspiratory time period; Integrate the inspiratory flow rate during the effective inspiratory time period to obtain the effective inhaled volume; The ratio of effective inspired volume to the subjects’ forced vital capacity was calculated; According to formula (2), if formula (2) is satisfied, the deep inhalation technique is judged to be qualified; if formula (2) is not satisfied, the deep inhalation technique is judged to be unqualified: (2)； in: Indicates the effective inhalation time. Indicates the inhalation time threshold of the inhalation device. Indicates the effective suction volume, represents the inspiratory volume threshold, represents the forced vital capacity of the subject, Indicates the inspiratory volume ratio threshold.

8. The artificial intelligence management method for inhalation-type drugs according to claim 1 is characterized in that: In step D23, the following method is used to determine whether the initial acceleration of inhalation of the passive mist-releasing inhalation device is qualified: The optimal inhalation flow rate during the inhalation period and the time required to reach the optimal inhalation flow rate are extracted, the inhalation starting acceleration is calculated, and the inhalation starting acceleration is compared with the inhalation starting acceleration setting threshold. If the calculated inhalation starting acceleration is greater than or equal to the inhalation starting acceleration setting threshold, the inhalation starting acceleration used by the passive mist release inhalation device is judged to be qualified. If the calculated inhalation starting acceleration is less than the inhalation starting acceleration setting threshold, the inhalation starting acceleration used by the passive mist release inhalation device is judged to be unqualified.

9. The artificial intelligence management method for inhalation-type drugs according to claim 1 is characterized in that: The inhalation technique training model includes the following steps: E1: The virtual digital human animation demonstrates the use steps of various types of inhalation devices and the technical requirements of each step. The patient watches the digital human animation demonstration and uses the inhalation drug device according to the operating instructions; E2: The inhalation technique training and detection module determines whether the patient's inhalation technique performance using the inhalation device meets the standard based on the inhalation technique quantitative evaluation model, and indicates the category of inhalation technique errors when the inhalation technique performance does not meet the standard; E3: The enhanced feedback module for inhalation technique training displays the patient's inhalation technique performance to the operator and the patient and generates an evaluation report. Based on the feedback, the patient's behavioral movements for using the inhalation device are repeatedly trained until the inhalation technique performance meets the standard.

10. The artificial intelligence management method for inhalation-type drugs according to claim 1, characterized in that: In step F3, the actual inhalation medication compliance is calculated according to formula (3): : （3）； in: Indicates the actual number of medications taken during the planned medication period. The proportion of patients who performed the inhalation technique correctly during the planned medication period, Indicates the total number of planned medication doses.

11. The artificial intelligence management method for inhalation-type drugs according to claim 2, characterized in that: The data statistics display model comprises the following steps: G1: The data statistics module classifies and counts the data generated by the inhalation capacity assessment model, the inhalation technology quantitative assessment model, the inhalation technology training model, and the daily inhalation medication management model in the stable period, and performs secondary processing to form charts; G2: The data display module summarizes and displays data in the form of charts.

12. An artificial intelligence management system for inhaled drugs, characterized by: Used to execute an artificial intelligence management method based on inhalation-type drugs as described in any one of claims 1 to 11, which includes an inhalation ability evaluation unit, an inhalation technology quantitative evaluation unit, an inhalation technology training unit and a stable period daily inhalation management unit connected in sequence, the inhalation ability evaluation unit is used to evaluate whether the subject has reached the inhalation ability required by the passive mist release inhalation device; the inhalation technology quantitative evaluation unit is used to evaluate whether the subject's action behavior when using inhaled drugs meets the technical requirements of the inhalation device, and identify the category of technical errors; the inhalation technology training unit uses digital human intelligent interaction technology to simulate and replace the medical staff's drug teaching interaction scene; the stable period daily inhalation management unit is used to apply the inhalation technology quantitative evaluation model to the subject's stable period daily inhalation medication management.

13. The artificial intelligence management system based on inhalation type drugs according to claim 12, characterized in that: The inhalation ability assessment unit includes an inhalation ability assessment data acquisition module, an inhalation ability assessment analysis module and an inhalation ability assessment feedback display module; the inhalation technology quantitative assessment unit includes an inhalation technology quantitative assessment data acquisition module and an inhalation technology quantitative assessment data analysis module; the inhalation technology training unit includes a virtual digital human, an inhalation technology training detection module and an inhalation technology training enhanced feedback module; the stable period daily inhalation management unit includes a stable period daily inhalation medication management detection module, a scale collection module, a stable period daily inhalation medication management data analysis module and a stable period daily inhalation medication management enhanced feedback module.

14. The artificial intelligence management system for inhaled drugs according to claim 12, characterized in that: It also includes a data statistics display unit, which includes a data statistics module and a data presentation module.

Images